DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Priority
Receipt is acknowledged of certified copies of papers submitted under 35 U.S.C. 119(a)-(d), which papers have been placed of record in the file.
Response to Remark(s)
Applicant's amendment filed March 29th, 2026 have been fully entered and considered. Applicant’s amendment to the claims have overcome the 112 (f) interpretation, 112(a) and 112(b) rejections previously set forth in the Non-Final Office Action mailed on February 10th, 2026. The amendment has changed the scope of the claims, updated search has resulted in prior arts that teaches the amended claims and the previously allowed claims, thus previous Office action has been vacated and new grounds of rejection set forth in the present action as set forth below. Accordingly, this action is made non-final.
Status of Claims
Claims 1-20 are pending, claims 1-12, 14 and 18-19 have been amended. Claims 1-20 remains rejected.
Response to Argument(s)
The Applicants’ amendments, argument/remarks have been fully considered. In view of the Amendments to independent claims 1 and 14, which have changed and narrowed down the scope of the claim, updated search has resulted in newly found prior arts to reflect the previously allowed claims, therefore, the previously allowed claims 13 and 20 are now rejected under prior art rejection. The previous Office action has been vacated and new grounds of rejections are set forth under a second Non-final rejection, for the claims 1-20, as described below.
Claim Objections
Claims 1, 5-6, 9, 14 and 18-19 are objected to because of the following informalities:
Claim 1, line 2, “circuitry configured to” should be read as “a circuitry configured to:” to follow proper claim language and formality so since the circuitry here being recited to perform multiple steps of the claim, needs to have a “:”. Appropriate correction is required.
Claim 5, line 3, “the circuitry configured to” should be read as “the circuitry configured to:” to follow proper claim language and formality so since the circuitry here being recited to perform multiple steps of the claim, needs to have a “:”. Appropriate correction is required.
Claim 6, line 3, “the circuitry configured to” should be read as “the circuitry configured to:” to follow proper claim language and formality so since the circuitry here being recited to perform multiple steps of the claim, needs to have a “:”. Appropriate correction is required.
Claim 9, line 3, “the circuitry configured to” should be read as “the circuitry configured to:” to follow proper claim language and formality so since the circuitry here being recited to perform multiple steps of the claim, needs to have a “:”. Appropriate correction is required.
Claim 14, line 2, “circuitry configured to” should be read as “a circuitry configured to:” to follow proper claim language and formality so since the circuitry here being recited to perform multiple steps of the claim, needs to have a “:”. Appropriate correction is required.
Claim 18, line 3, “the circuitry configured to” should be read as “the circuitry configured to:” to follow proper claim language and formality so since the circuitry here being recited to perform multiple steps of the claim, needs to have a “:”. Appropriate correction is required.
Claim 19, line 3, “the circuitry configured to” should be read as “the circuitry configured to:” to follow proper claim language and formality so since the circuitry here being recited to perform multiple steps of the claim, needs to have a “:. Appropriate correction is required.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-2, 9-10, 13-15 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Rajan Laxman Joshi et.al., (“US 2021/0104074 A1,” hereinafter as “Joshi”) in view of Sejin OH (“US 2021/0319571 A1” hereinafter as “OH”).
Regarding claim 1, Joshi explicitly teaches an information processing device comprising (Title and Abstract):
circuitry configured to (Par. [0010] discloses the process of the invention to be executed by a processor)
decode a bitstream (Par. [0092] discloses “a decoder receives a bitstream…” indicating decoding of a bitstream) obtained by dividing a mesh that represents an object (Par. [0092] discloses “…a bitstream that includes the frames and….the geometry of the 3D point cloud;” furthermore, Par. [0095] discloses “a point cloud or a mesh can represent a single object” indicating that the point cloud data being decoded is a mesh of an object) with a three-dimensional structure (as discussed previously, in Par. [0092], the point cloud data being 3D point cloud data) into at least a first patch and a second patch (Par. [0091] discloses “clusters of points that are not next to each other in 3D space could be represented as patches that are adjacent to one another in the frames” indicating patches, any of which is analogous to the recited first patch and the other to be the recited second patch), placing the first patch and the second patch within a single image (Par. [0049] discloses “two patches that are not next to each other on the 3D point cloud can be packed next to each other in a single frame,” in this instance, any one of the two patches would be analogous to the recited first patch and the other to be the recited second patch), and encoding the single image (Par. [0044] discloses “an encoder….points as patches on a 2D frames…encode the geometry information” indicating encoding of the frame including the patches);
execute a boundary correction process (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process]) to correct a geometry for a boundary point located at a boundary of the patches decoded (Par. [0050] discloses “perform…geometry smoothing” indicating the smoothing is to smooth geometry information, as discussed previously, the smoothing is performed on the 3D point cloud of patch boundary indicating the boundary of the patches; moreover, Par. [0167] discloses “a boundary point is located within the cell, the cell as well as seven neighboring cells of the cell…a boundary point is located within the portion of the cell…and the cell that touches the bottom left corner of the portion of the cell”; furthermore, Par. [0211] discloses “each of the points have an (x,y) location…the point is a boundary point…the boundary point is located on the bottom left corner of the cell” therefore, indicating the boundary point is a corner point, which is analogous to the recited boundary point [corner point of a boundary] to be performed to boundary correction process on as discussed); and
set the boundary point subjected to the boundary correction process as a reference point (Par. [0050] discloses “boundary points to be smoothed” indicating the boundary points are being set as reference for the correction process; moreover, Par. [0211] discloses “each of the points have an (x,y) location…the point is a boundary point…the boundary point is located on the bottom left corner of the cell” therefore, indicating the boundary point is a corner point, which is analogous to the recited boundary vertex to be performed to boundary correction process on as discussed, therefore, the boundary points being boundary point [corner point of a boundary] as the reference for the correction process) and executes a smoothing process to smooth a geometry for a point within a partial area based on the reference point (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process] of a partial area; Par. [0211] discloses “each of the points have an (x,y) location…the point is a boundary point…the boundary point is located on the bottom left corner of the cell” therefore, indicating the boundary point is a corner point, which is analogous to the recited boundary point to be performed to boundary correction process on as discussed, therefore, the boundary points being boundary point [corner point of a boundary] as the reference for the correction process).
However, Joshi is silent on the boundary point being a boundary vertex; and the geometry for a point being geometry for a vertex.
In the same field of transmitting and processing point cloud data as bitstream (Abstract, OH), OH explicitly the boundary point being a boundary vertex (Par. [0109] discloses “render the decoded point cloud data…render the geometry and attributes decoded through the decoding process…points in the point cloud content may be rendered to a vertex having a certain thickness, a cube having a specific minimum size centered on the corresponding vertex position” indicating that the decoded point cloud can be rendered in vertices; moreover, Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B; Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B.); and the geometry for a point being geometry for a vertex (Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B; furthermore, Par. [0105] discloses “the point cloud data may include the geometry and attributes of a point” indicating that the vertex also has geometry such as claimed. Therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of the vertex to represent the corner point of a block voxel structure, of a point cloud data set, to then be for further processing such as executing a smoothing process to smooth a geometry for a point vertex. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices [Par. 0003 of OH] to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi of a device to decode a bitstream obtained by dividing a mesh that represents an object with a three-dimensional structure into at least a first patch and a second patch, placing the first patch and the second patch within a single image, and encoding the single image and execute a boundary correction process to correct a geometry for a boundary point located at a boundary of the patches decoded and set the boundary point subjected to the boundary correction process as a reference point and executes a smoothing process to smooth a geometry for a point within a partial area based on the reference point. Moreover, Joshi’s boundary point can be modified to be rendered and represented as vertex with geometry information being rendered representative point of a point cloud as taught in OH.
Such a modification is the result of combing prior art elements. Joshi and OH share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing device comprising circuitry configured to decode a bitstream obtained by dividing a mesh that represents an object with a three-dimensional structure into at least a first patch and a second patch, placing the first patch and the second patch within a single image, and encoding the single image; execute a boundary correction process to correct a geometry for a boundary vertex located at a boundary of the patches decoded; and set the boundary vertex subjected to the boundary correction process as a reference point and executes a smoothing process to smooth a geometry for a vertex within a partial area based on the reference point. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices, see Par. [0003] of OH, to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH.
Regarding claim 2, Joshi in view of OH, in combination, explicitly teaches the information processing device according to claim 1, wherein Joshi explicitly teaches
the circuitry is configured to set the reference point on a basis of geometry of the boundary point subjected to the boundary correction process (Par. [0050] discloses “boundary points to be smoothed” indicating the boundary points are being set as reference for the correction process; Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process] of a partial area; Par. [0211] discloses “each of the points have an (x,y) location…the point is a boundary point…the boundary point is located on the bottom left corner of the cell” therefore, indicating the boundary point is a corner point, which is analogous to the recited boundary vertex to be performed to boundary correction process on as discussed, therefore, the boundary points being boundary point [corner point of the boundary] as the reference for the correction process based on its geometry).
However, Joshi is silent on the boundary point being a boundary vertex.
In the same field of transmitting and processing point cloud data as bitstream (Abstract, OH), OH explicitly teaches the boundary point being a boundary vertex (Par. [0101] discloses “the elements of the point cloud content providing system illustrated in FIG. 1 may be implemented by…a processor” being analogous to the circuitry; moreover, Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B; furthermore, Par. [0105] discloses “the point cloud data may include the geometry and attributes of a point” indicating that the vertex also has geometry such as claimed. Therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of the vertex to represent the corner point of a block voxel structure to then be for further processing such as setting the reference point on a basis of geometry of the boundary vertex subjected to the boundary correction process. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices [Par. 0003 of OH] to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi of a device to process point cloud data by setting a reference point on a basis of geometry of a boundary point subjected to a boundary correction process. Moreover, Joshi’s boundary point can be modified to be rendered and represented as vertex with geometry information being rendered representative point of a point cloud as taught in OH.
Such a modification is the result of combing prior art elements. Joshi and OH share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing device comprising circuitry configured to obtain reference point from a point cloud data, set the reference point on a basis of geometry of the boundary vertex subjected to a boundary correction process. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices, see Par. [0003] of OH, to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH.
Regarding claim 9, Joshi in view of OH, in combination, explicitly teaches the information processing device according to claim 1, wherein Joshi explicitly teaches
the circuitry is further configured to (Par. [0010] discloses the process of the invention to be executed by a processor)
acquire smoothing information including transmitted information regarding the smoothing (Par. [0050] discloses “geometry smoothing…the boundary points can be smoothed to remove the visual artifact and thereby increasing the visual appearance of the point cloud…boundary points to be smoothed…by deriving the centroid for only the boundary cells” indicating the boundary points are being set as reference for the correction process, the centroid here is analogous to the recited correction utilization point, since it’s being used to perform the smoothing of the boundary points [utilization for correction], the point cloud here is being processed for the smoothing to increase visual appearance, therefore, any point within the point cloud is being analogous to the correction target point as claimed for a geometry smoothing process; moreover, Par. [0103] discloses “the encoder transmits frames representing the point cloud as an encoded bitstream” to be processed by the decoder, this transmitted information is required for the smoothing process, hence, is analogous to the smoothing information as claimed being acquired by the decoder), and
execute the smoothing process on a basis of the smoothing information acquired (Par. [0092] discloses “a decoder receives a bitstream…” indicating decoding of a bitstream, being the transmitted smoothing information, the decoder to perform the smoothing process on the transmitted smoothing information acquired).
Regarding claim 10, Joshi in view of OH, in combination, explicitly teaches the information processing device according to claim 9, wherein Joshi explicitly teaches
the circuitry is configured to (Par. [0010] discloses the process of the invention to be executed by a processor)
set the reference point by a method indicated by the smoothing information (Par. [0050] discloses “boundary points to be smoothed” indicating the boundary points are being set as reference for the correction process; moreover, Par. [0211] discloses “each of the points have an (x,y) location…the point is a boundary point…the boundary point is located on the bottom left corner of the cell” therefore, indicating the boundary point is a corner point, which is analogous to the recited boundary vertex to be performed to boundary correction process on as discussed, therefore, the boundary points being boundary vertex [corner point] as the reference for the correction process; and is based on the transmitted information being required for the smoothing, being the bitstream and the smoothing process is based on the determination if the bitstream data needs to be smoothed or not according to Par. [0143] disclosing “find the smoothed geometry for each boundary point. The smoothing engine determines whether the distance between a single boundary point and the filter output is larger than a threshold….when the distance between a single boundary point and the filter output is less than the threshold, the smoothing engine determines that no geometry smoothing is necessary for the boundary point” which results in the suitable method for smoothing).
Regarding claim 13, Joshi explicitly teaches an information processing method comprising (Title and Abstract):
decoding a bitstream (Par. [0092] discloses “a decoder receives a bitstream…” indicating decoding of a bitstream) obtained by dividing a mesh that represents an object (Par. [0092] discloses “…a bitstream that includes the frames and….the geometry of the 3D point cloud;” furthermore, Par. [0095] discloses “a point cloud or a mesh can represent a single object” indicating that the point cloud data being decoded is a mesh of an object) with a three-dimensional structure (as discussed previously, in Par. [0092], the point cloud data being 3D point cloud data) into at least a first patch and a second patch (Par. [0091] discloses “clusters of points that are not next to each other in 3D space could be represented as patches that are adjacent to one another in the frames” indicating patches, any of which is analogous to the recited first patch and the other to be the recited second patch), placing the first patch and the second patch within a single image (Par. [0049] discloses “two patches that are not next to each other on the 3D point cloud can be packed next to each other in a single frame,” in this instance, any one of the two patches would be analogous to the recited first patch and the other to be the recited second patch), and encoding the single image (Par. [0044] discloses “an encoder….points as patches on a 2D frames…encode the geometry information” indicating encoding of the frame including the patches);
executing a boundary correction process (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process]) to correct a geometry for a boundary point located at a boundary of the patches decoded (Par. [0050] discloses “perform…geometry smoothing” indicating the smoothing is to smooth geometry information, as discussed previously, the smoothing is performed on the 3D point cloud of patch boundary indicating the boundary of the patches; moreover, Par. [0167] discloses “a boundary point is located within the cell, the cell as well as seven neighboring cells of the cell…a boundary point is located within the portion of the cell…and the cell that touches the bottom left corner of the portion of the cell”; furthermore, Par. [0211] discloses “each of the points have an (x,y) location…the point is a boundary point…the boundary point is located on the bottom left corner of the cell” therefore, indicating the boundary point is a corner point, which is analogous to the recited boundary vertex [corner point] to be performed to boundary correction process on as discussed); and
setting the boundary point subjected to the boundary correction process as a reference point (Par. [0050] discloses “boundary points to be smoothed” indicating the boundary points are being set as reference for the correction process; moreover, Par. [0211] discloses “each of the points have an (x,y) location…the point is a boundary point…the boundary point is located on the bottom left corner of the cell” therefore, indicating the boundary point is a corner point, which is analogous to the recited boundary vertex to be performed to boundary correction process on as discussed, therefore, the boundary points being boundary vertex [corner point] as the reference for the correction process) and executes a smoothing process to smooth a geometry for a point within a partial area based on the reference point (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process] of a partial area; Par. [0211] discloses “each of the points have an (x,y) location…the point is a boundary point…the boundary point is located on the bottom left corner of the cell” therefore, indicating the boundary point is a corner point, which is analogous to the recited boundary vertex to be performed to boundary correction process on as discussed, therefore, the boundary points being boundary vertex [corner point] as the reference for the correction process).
However, Joshi is silent on the boundary point being a boundary vertex; and the geometry for a point being geometry for a vertex.
In the same field of transmitting and processing point cloud data as bitstream (Abstract, OH), OH explicitly the boundary point being a boundary vertex (Par. [0109] discloses “render the decoded point cloud data…render the geometry and attributes decoded through the decoding process…points in the point cloud content may be rendered to a vertex having a certain thickness, a cube having a specific minimum size centered on the corresponding vertex position” indicating that the decoded point cloud can be rendered in vertices; moreover, Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B; Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B.); and the geometry for a point being geometry for a vertex (Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B; furthermore, Par. [0105] discloses “the point cloud data may include the geometry and attributes of a point” indicating that the vertex also has geometry such as claimed. Therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of the vertex to represent the corner point of a block voxel structure, of a point cloud data set, to then be for further processing such as executing a smoothing process to smooth a geometry for a point vertex. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices [Par. 0003 of OH] to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi of a method to decode a bitstream obtained by dividing a mesh that represents an object with a three-dimensional structure into at least a first patch and a second patch, placing the first patch and the second patch within a single image, and encoding the single image and execute a boundary correction process to correct a geometry for a boundary point located at a boundary of the patches decoded and set the boundary point subjected to the boundary correction process as a reference point and executes a smoothing process to smooth a geometry for a point within a partial area based on the reference point. Moreover, Joshi’s boundary point can be modified to be rendered and represented as vertex with geometry information being rendered representative point of a point cloud as taught in OH.
Such a modification is the result of combing prior art elements. Joshi and OH share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing method to decode a bitstream obtained by dividing a mesh that represents an object with a three-dimensional structure into at least a first patch and a second patch, placing the first patch and the second patch within a single image, and encoding the single image; execute a boundary correction process to correct a geometry for a boundary vertex located at a boundary of the patches decoded; and set the boundary vertex subjected to the boundary correction process as a reference point and executes a smoothing process to smooth a geometry for a vertex within a partial area based on the reference point. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices, see Par. [0003] of OH, to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH.
Regarding claim 14, Joshi explicitly teaches an information processing device comprising (Title and Abstract):
circuitry configured to (Par. [0010] discloses the process of the invention to be executed by a processor)
use a boundary point subjected to a boundary correction process as a reference point (Par. [0050] discloses “boundary points to be smoothed” indicating the boundary points are being set as reference for the correction process) to generate smoothing information including information regarding a smoothing process (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process]) to smooth a geometry of a point within a partial area based on the reference point (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process] of a partial area); and
provide the smoothing information (Par. [0050] discloses “perform…geometry smoothing” indicating the smoothing is to smooth geometry information, as discussed previously, the smoothing is performed on the 3D point cloud of patch boundary indicating the boundary of the patches), wherein
the boundary point is at a boundary of a patch corresponding to a part of a mesh (Par. [0092] discloses “…a bitstream that includes the frames and….the geometry of the 3D point cloud;” furthermore, Par. [0095] discloses “a point cloud or a mesh can represent a single object” indicating that the point cloud data being decoded is a mesh of an object) that represents an object with a three-dimensional structure (as discussed previously, in Par. [0092], the point cloud data being 3D point cloud data), and
the boundary correction process is a process of correcting a geometry of the boundary point (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process]).
However, Joshi is silent on the boundary point being a boundary vertex; and the geometry for a point being geometry for a vertex.
In the same field of transmitting and processing point cloud data as bitstream (Abstract, OH), OH explicitly the boundary point being a boundary vertex (Par. [0109] discloses “render the decoded point cloud data…render the geometry and attributes decoded through the decoding process…points in the point cloud content may be rendered to a vertex having a certain thickness, a cube having a specific minimum size centered on the corresponding vertex position” indicating that the decoded point cloud can be rendered in vertices; moreover, Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B; Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B.); and the geometry for a point being geometry for a vertex (Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B; furthermore, Par. [0105] discloses “the point cloud data may include the geometry and attributes of a point” indicating that the vertex also has geometry such as claimed. Therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of the vertex to represent the corner point of a block voxel structure, of a point cloud data set, to then be for further processing such as executing a smoothing process to smooth a geometry for a point vertex. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices [Par. 0003 of OH] to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi of an information processing device comprising circuitry configured to use a boundary point subjected to a boundary correction process as a reference point to generate smoothing information including information regarding a smoothing process to smooth a geometry of a point within a partial area based on the reference point; and provide the smoothing information, wherein the boundary point is a vertex located at a boundary of a patch corresponding to a part of a mesh that represents an object with a three-dimensional structure, and the boundary correction process is a process of correcting a geometry of the boundary point. Moreover, Joshi’s boundary point can be modified to be rendered and represented as vertex with geometry information being rendered representative point of a point cloud as taught in OH.
Such a modification is the result of combing prior art elements. Joshi and OH share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have An information processing device comprising circuitry configured to use a boundary vertex subjected to a boundary correction process as a reference point to generate smoothing information including information regarding a smoothing process to smooth a geometry of a vertex within a partial area based on the reference point; and provide the smoothing information, wherein the boundary vertex is a vertex located at a boundary of a patch corresponding to a part of a mesh that represents an object with a three-dimensional structure, and the boundary correction process is a process of correcting a geometry of the boundary vertex. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices, see Par. [0003] of OH, to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH.
Regarding claim 15, Joshi in view of OH in combination explicitly teaches the information processing device according to claim 14, wherein Joshi explicitly teaches
the smoothing information includes information for specifying a point to be used as the reference point (Par. [0050] discloses “geometry smoothing…the boundary points can be smoothed to remove the visual artifact and thereby increasing the visual appearance of the point cloud…boundary points to be smoothed…by deriving the centroid for only the boundary cells” indicating the boundary points are being set as reference for the correction process, the centroid here is analogous to the recited correction utilization point, since it’s being used to perform the smoothing of the boundary points [utilization for correction], the point cloud here is being processed for the smoothing to increase visual appearance, therefore, any point within the point cloud is being analogous to the correction target point as claimed for a geometry smoothing process; moreover, Par. [0103] discloses “the encoder transmits frames representing the point cloud as an encoded bitstream” to be processed by the decoder, this transmitted information is required for the smoothing process, hence, is analogous to the smoothing information as claimed being acquired by the decoder, including data to be determined the vertex to be smoothed).
However, Joshi is silent on the point being a vertex.
In the same field of transmitting and processing point cloud data as bitstream (Abstract, OH), OH explicitly teaches the point being a vertex (Par. [0101] discloses “the elements of the point cloud content providing system illustrated in FIG. 1 may be implemented by…a processor” being analogous to the circuitry; moreover, Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B; furthermore, Par. [0105] discloses “the point cloud data may include the geometry and attributes of a point” indicating that the vertex also has geometry such as claimed. Therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of the vertex to represent the corner point of a block voxel structure to then be for further processing. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices [Par. 0003 of OH] to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi of a device to have a smoothing information includes information for specifying a point to be used as the reference point. Moreover, Joshi’s boundary point can be modified to be rendered and represented as vertex with geometry information being rendered representative point of a point cloud as taught in OH.
Such a modification is the result of combing prior art elements. Joshi and OH share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing device comprising: circuitry configured to use a boundary vertex subjected to a boundary correction process as a reference point to generate smoothing information including information regarding a smoothing process to smooth a geometry of a vertex within a partial area based on the reference point. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices, see Par. [0003] of OH, to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH.
Regarding claim 18, Joshi in view of OH in combination explicitly teaches the information processing device according to claim 14, wherein Joshi explicitly teaches
the circuitry is further configured to (Par. [0010] discloses the process of the invention to be executed by a processor)
execute the boundary correction process (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process] of a partial area; Par. [0211] discloses “each of the points have an (x,y) location…the point is a boundary point…the boundary point is located on the bottom left corner of the cell” therefore, indicating the boundary point is a corner point, which is analogous to the recited boundary vertex to be performed to boundary correction process on as discussed, therefore, the boundary points being boundary vertex [corner point] as the reference for the correction process), wherein and
generate the smoothing information on a basis of the geometry of the boundary point subjected to the boundary correction process (Par. [0050] discloses “boundary points to be smoothed” indicating the boundary points are being set as reference for the correction process; moreover, Par. [0211] discloses “each of the points have an (x,y) location…the point is a boundary point…the boundary point is located on the bottom left corner of the cell” therefore, indicating the boundary point is a corner point, which is analogous to the recited boundary vertex to be performed to boundary correction process on as discussed, therefore, the boundary points being boundary vertex [corner point] as the reference for the correction process, hence the smoothing data being generated is for smoothing of the geometry of the boundary vertex which is subject to the correction process; Par. [0050] discloses “perform…geometry smoothing” indicating the smoothing is to smooth geometry information, as discussed previously, the smoothing is performed on the 3D point cloud of patch boundary indicating the boundary of the patches; moreover, Par. [0167] discloses “a boundary point is located within the cell, the cell as well as seven neighboring cells of the cell…a boundary point is located within the portion of the cell…and the cell that touches the bottom left corner of the portion of the cell”; furthermore, Par. [0211] discloses “each of the points have an (x,y) location…the point is a boundary point…the boundary point is located on the bottom left corner of the cell” therefore, indicating the boundary point is a corner point, which is analogous to the recited boundary vertex [corner point] to be performed to boundary correction process on as discussed).
However, Joshi is silent on the boundary point being a boundary vertex.
In the same field of transmitting and processing point cloud data as bitstream (Abstract, OH), OH explicitly teaches the boundary point being a boundary vertex (Par. [0101] discloses “the elements of the point cloud content providing system illustrated in FIG. 1 may be implemented by…a processor” being analogous to the circuitry; moreover, Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B; furthermore, Par. [0105] discloses “the point cloud data may include the geometry and attributes of a point” indicating that the vertex also has geometry such as claimed. Therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of the vertex to represent the corner point of a block voxel structure to then be for further processing such as to generate the smoothing information on a basis of the geometry of the boundary point subjected to the boundary correction process. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices [Par. 0003 of OH]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi of a device of performing generating a smoothing information on a basis of a geometry of a boundary vertex subjected to the boundary correction process. Moreover, Joshi’s boundary point can be modified to be rendered and represented as vertex with geometry information being rendered representative point of a point cloud as taught in OH.
Such a modification is the result of combing prior art elements. Joshi and OH share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have An information processing device comprising circuitry configured to use a boundary vertex subjected to a boundary correction process as a reference point to generate smoothing information including information regarding a smoothing process to smooth a geometry of a vertex within a partial area based on the reference point; and provide the smoothing information, wherein the boundary vertex is a vertex located at a boundary of a patch corresponding to a part of a mesh that represents an object with a three-dimensional structure, and the boundary correction process is a process of correcting a geometry of the boundary vertex, wherein the boundary point can be modified to be rendered and represented as vertex with geometry information being rendered representative point of a point cloud. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices, see Par. [0003] of OH, to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH.
Regarding claim 19, Joshi in view of OH in combination explicitly teaches the information processing device according to claim 14, wherein Joshi explicitly teaches
the circuitry is further configured to (Par. [0010] discloses the process of the invention to be executed by a processor)
generate boundary correction information regarding the boundary correction process, and (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process] such as discussed, Par. [0050] discloses “boundary points to be smoothed” indicating the boundary points are being set as reference for the correction process; moreover, Par. [0044] discloses “stores the groups of points as patches on a 2D frames…to encode the geometry information…based on a location (U,V) of a pixel in the geometry frame corresponds to a (X,Y,X) location of a point in 3D space” indicating the geometry information being in 2D coordinate, therefore, the geometry smoothing of the points of the point cloud is a smoothing process on 2D coordinates of the points; and the “location (U,V)” is analogous to the recited “on a basis of position correction coordinate information”)
generate the smoothing information on a basis of the boundary correction information (Par. [0143] discloses “find the smoothed geometry for each boundary point. The smoothing engine determines whether the distance between a single boundary point and the filter output is larger than a threshold….when the distance between a single boundary point and the filter output is less than the threshold, the smoothing engine determines that no geometry smoothing is necessary for the boundary point” indicating that the geometry smoothing is based on a filter output, being smoothing geometry for each boundary point; therefore, the filter output is analogous to the recited “geometry after correction”).
Regarding claim 20, Joshi explicitly teaches an information processing method comprising (Title and Abstract):
setting a boundary point subjected to a boundary correction process as a reference point (Par. [0050] discloses “boundary points to be smoothed” indicating the boundary points are being set as reference for the correction process), and generating smoothing information including information regarding a smoothing process (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process]) to smooth a geometry of a point within a partial area based on the reference point (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process] of a partial area); and
providing the smoothing information (Par. [0050] discloses “perform…geometry smoothing” indicating the smoothing is to smooth geometry information, as discussed previously, the smoothing is performed on the 3D point cloud of patch boundary indicating the boundary of the patches), wherein
the boundary point is a point located at a boundary of a patch corresponding to a part of a mesh (Par. [0092] discloses “…a bitstream that includes the frames and….the geometry of the 3D point cloud;” furthermore, Par. [0095] discloses “a point cloud or a mesh can represent a single object” indicating that the point cloud data being decoded is a mesh of an object) that represents an object with a three-dimensional structure (as discussed previously, in Par. [0092], the point cloud data being 3D point cloud data), and
the boundary correction process is a process of correcting a geometry of the boundary point (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process]).
However, Joshi is silent on the boundary point being a boundary vertex; and the geometry if a geometry of a vertex and the point being a vertex.
In the same field of transmitting and processing point cloud data as bitstream (Abstract, OH), OH explicitly teaches the boundary point being a boundary vertex (Par. [0109] discloses “render the decoded point cloud data…render the geometry and attributes decoded through the decoding process…points in the point cloud content may be rendered to a vertex having a certain thickness, a cube having a specific minimum size centered on the corresponding vertex position” indicating that the decoded point cloud can be rendered in vertices; moreover, Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B); and the geometry if a geometry of a vertex and the point being a vertex (Par. [0109] discloses “render the decoded point cloud data…render the geometry and attributes decoded through the decoding process…points in the point cloud content may be rendered to a vertex having a certain thickness, a cube having a specific minimum size centered on the corresponding vertex position” indicating that the decoded point cloud can be rendered in vertices; moreover, Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B; Therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of the vertex to represent the corner point of a block voxel structure, of a point cloud data set, to then be for further processing such as executing a smoothing process to smooth a geometry for a point vertex. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices [Par. 0003 of OH] to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi of an information processing method comprising setting a boundary point subjected to a boundary correction process as a reference point, and generating smoothing information including information regarding a smoothing process to smooth a geometry of a point within a partial area based on the reference point; and providing the smoothing information, wherein the boundary point is a point located at a boundary of a patch corresponding to a part of a mesh that represents an object with a three-dimensional structure, and the boundary correction process is a process of correcting a geometry of the boundary point. Moreover, Joshi’s boundary point can be modified to be rendered and represented as vertex with geometry information being rendered representative point of a point cloud as taught in OH.
Such a modification is the result of combing prior art elements. Joshi and OH share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing method comprising: setting a boundary vertex subjected to a boundary correction process as a reference point, and generating smoothing information including information regarding a smoothing process to smooth a geometry of a vertex within a partial area based on the reference point; and providing the smoothing information, wherein the boundary vertex is a vertex located at a boundary of a patch corresponding to a part of a mesh that represents an object with a three-dimensional structure, and the boundary correction process is a process of correcting a geometry of the boundary vertex. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices, see Par. [0003] of OH, to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH.
Claims 3-8, 11-12 and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over Rajan Laxman Joshi et.al., (“US 2021/0104074 A1,” hereinafter as “Joshi”) in view of Sejin OH (“US 2021/0319571 A1” hereinafter as “OH”) and Khaled Mammou et. al. (“US 2019/0311501 A1” hereinafter as “Mammou”)
Regarding claim 3, Joshi in view of OH in combination explicitly teaches the information processing device according to claim 2, wherein Joshi explicitly teaches
the circuitry is configured to (Par. [0010] discloses the process of the invention to be executed by a processor)
set a point to be subjected to the smoothing process and a correction utilization point to be used in the smoothing process on a basis of the set reference point (Par. [0050] discloses “geometry smoothing…the boundary points can be smoothed to remove the visual artifact and thereby increasing the visual appearance of the point cloud…boundary points to be smoothed…by deriving the centroid for only the boundary cells” indicating the boundary points are being set as reference for the correction process, the centroid here is analogous to the recited correction utilization point, since it’s being used to perform the smoothing of the boundary points [utilization for correction], moreover, Par. [0047] discloses “the 3D point cloud can be smoothed to improve the visual quality of the 3D point cloud” indicating the point cloud here is being processed for the smoothing to increase visual appearance, therefore, any point within the point cloud is being analogous to the point as claimed subjected for the smoothing process).
However, Joshi in view of OH in combination is silent on a process to set a correction target point to be subjected to the smoothing process.
In the same field of point cloud smoothing (Title and Abstract, Mammou), Mammou explicitly teaches to set a correction target point to be subjected to the smoothing process (Par. [0307] discloses “a balance may be reaches between quality of a reconstructed point cloud and efficiency, wherein more quantization increases compression efficiency and less quantization creases quality…an update operator may smooth residual differences, e.g. predicted attribute values that are used to determine attribute correction values, in order to increase compression efficiency while taking into account relative influence or important of points when smoothing the residual differences” indicating point cloud points subjected to smoothing [analogous to the recited smoothing process] for reconstruction and data compression, correction values are being used for the smoothing process, which the correction values here are values of the point cloud points, Par. [0311] discloses “attribute correction values for the attributes of the points”; Therefore, the correction values of the points are analogous to the recited correction target point; therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of a target correction point representing attributes of the point cloud points being subject to a smoothing process as a result of reconstruction and compression. Thus in order to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality [paragraph 0307 of Mammou]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi in view of OH in combination of a processing device with a circuitry is configured to set a point to be subjected to the smoothing process and a correction utilization point to be used in the smoothing process on a basis of the set reference point as taught in Joshi. Moreover, Joshi’s point that is subjected to the smoothing process can be modified to be corrected with attribute correction values representing the attributes of the points before being subject to the smoothing process as taught in Mammou.
Such a modification is the result of combing prior art elements. Joshi, OH and Mammou share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing device comprising circuitry configured to obtain reference point from a point cloud data, set the reference point on a basis of geometry of the boundary vertex subjected to a boundary correction process, wherein the circuitry is configured to set a correction target point to be subjected to the smoothing process and a correction utilization point to be used in the smoothing process on a basis of the set reference point. Thus in order to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality (paragraph [0307] of Mammou).
Regarding claim 4, Joshi in view of OH and Mammou in combination explicitly teaches the information processing device according to claim 3, wherein Joshi explicitly teaches
the circuitry is configured to (Par. [0010] discloses the process of the invention to be executed by a processor)
correct three-dimensional coordinates of the point as the smoothing process (Par. [0050] discloses “geometry smoothing…of the reconstructed 3D point cloud…the boundary points can be smoothed to remove the visual artifact and thereby increasing the visual appearance of the point cloud…boundary points to be smoothed…by deriving the centroid for only the boundary cells” indicating the point cloud here is being processed for the smoothing to increase visual appearance, therefore, any point within the point cloud is being analogous to the correction target point as claimed which is in 3D; furthermore, Par. [0043] discloses “the points of the 3D point cloud that are represented…positioned at over the same coordinates. For example, a pixel at the position (u,v) in a frame…such as a geometric position of the points in 3D space” and Par. [0044] discloses “stores the groups of points as patches on a 2D frames…to encode the geometry information…based on a location (U,V) of a pixel in the geometry frame corresponds to a (X,Y,X) location of a point in 3D space” indicating the points being in 3D space coordinate, hence, the smoothing can be understood to be performed on 3D coordinates).
However, Joshi in view of OH in combination is silent on a process to correct three-dimensional coordinates of the target correction point as the smoothing process.
In the same field of point cloud smoothing (Title and Abstract, Mammou), Mammou explicitly teaches to correct three-dimensional coordinates of the target correction point as the smoothing process (Par. [0307] discloses “a balance may be reaches between quality of a reconstructed point cloud and efficiency, wherein more quantization increases compression efficiency and less quantization creases quality…an update operator may smooth residual differences, e.g. predicted attribute values that are used to determine attribute correction values, in order to increase compression efficiency while taking into account relative influence or important of points when smoothing the residual differences” indicating point cloud points subjected to smoothing [analogous to the recited smoothing process] for reconstruction and data compression, correction values are being used for the smoothing process, which the correction values here are values of the point cloud points, Par. [0311] discloses “attribute correction values for the attributes of the points” also indicating that the correction values are values of the attributes of the points in 3D space with coordinates, Par. [0173] discloses “locations of points in 3D space, such as X, Y, and Z coordinates of the points”; therefore, the correction values of the points are analogous to the recited correction target point representing the points in 3D space with 3D coordinates; Therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of a target correction point representing attributes of the point cloud points being subject to a smoothing process of its 3D coordinate data, as a result of reconstruction and compression. Thus in order to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality [paragraph 0307 of Mammou]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi in view of OH in combination of an information processing device with a circuitry is configured to correct three-dimensional coordinates of the point as the smoothing process as taught by Joshi. Moreover, Joshi’s point that is subjected to the smoothing process, on its 3D coordinate data, can be modified to be corrected with attribute correction values representing the attributes of the points before being subject to the smoothing process as taught in Mammou.
Such a modification is the result of combing prior art elements. Joshi, OH and Mammou share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing device comprising circuitry configured to obtain reference point from a point cloud data, set the reference point on a basis of geometry of the boundary vertex subjected to a boundary correction process, wherein the circuitry is configured to set a correction target point to be subjected to the smoothing process and a correction utilization point to be used in the smoothing process on a basis of the set reference point to correct three-dimensional coordinates of the target correction point as the smoothing process. Thus in order to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality (paragraph [0307] of Mammou).
Regarding claim 5, Joshi in view of OH and Mammou in combination explicitly teaches the information processing device according to claim 3, wherein Joshi explicitly teaches
the circuitry is configured to (Par. [0010] discloses the process of the invention to be executed by a processor)
correct two-dimensional coordinates of the boundary point as the boundary correction process (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process] such as discussed, Par. [0050] discloses “boundary points to be smoothed” indicating the boundary points are being set as reference for the correction process; moreover, Par. [0044] discloses “stores the groups of points as patches on a 2D frames…to encode the geometry information…based on a location (U,V) of a pixel in the geometry frame corresponds to a (X,Y,X) location of a point in 3D space” indicating the geometry information being in 2D coordinate, therefore, the geometry smoothing of the boundary points is boundary correction process on 2D coordinates of the points), and
correct two-dimensional coordinates of the point as the smoothing process (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process] such as discussed, Par. [0050] discloses “boundary points to be smoothed” indicating the boundary points are being set as reference for the correction process; moreover, Par. [0044] discloses “stores the groups of points as patches on a 2D frames…to encode the geometry information…based on a location (U,V) of a pixel in the geometry frame corresponds to a (X,Y,X) location of a point in 3D space” indicating the geometry information being in 2D coordinate, therefore, the geometry smoothing of the points of the point cloud is a smoothing process on 2D coordinates of the points).
However, Joshi is silent on the boundary point being a boundary vertex.
In the same field of transmitting and processing point cloud data as bitstream (Abstract, OH), OH explicitly teaches the boundary point being a boundary vertex (Par. [0101] discloses “the elements of the point cloud content providing system illustrated in FIG. 1 may be implemented by…a processor” being analogous to the circuitry; moreover, Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B; furthermore, Par. [0105] discloses “the point cloud data may include the geometry and attributes of a point” indicating that the vertex also has geometry such as claimed. Therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of the vertex to represent the corner point of a block voxel structure, of a point cloud data set, to then be for further processing such as executing a smoothing process to smooth a geometry for a point vertex. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices [Par. 0003 of OH] to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi of a device to correct two-dimensional coordinates of a boundary point as a boundary correction process, and correct two-dimensional coordinates of a correction target point as a smoothing process. Moreover, Joshi’s boundary point can be modified to be rendered and represented as vertex with geometry information being rendered representative point of a point cloud as taught in OH.
Such a modification is the result of combing prior art elements. Joshi and OH share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing device comprising circuitry configured to decode a bitstream obtained by dividing a mesh that represents an object with a three-dimensional structure into at least a first patch and a second patch, placing the first patch and the second patch within a single image, and encoding the single image; execute a boundary correction process to correct a geometry for a boundary vertex located at a boundary of the patches decoded; and set the boundary vertex subjected to the boundary correction process as a reference point and executes a smoothing process to smooth a geometry for a vertex within a partial area based on the reference point. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices, see Par. [0003] of OH, to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH.
However, Joshi in view of OH in combination is silent on a process to correct two-dimensional coordinates of the correction target point as the smoothing process.
In the same field of point cloud smoothing (Title and Abstract, Mammou), Mammou explicitly teaches to correct two-dimensional coordinates of the correction target point as the smoothing process (Par. [0307] discloses “a balance may be reaches between quality of a reconstructed point cloud and efficiency, wherein more quantization increases compression efficiency and less quantization creases quality…an update operator may smooth residual differences, e.g. predicted attribute values that are used to determine attribute correction values, in order to increase compression efficiency while taking into account relative influence or important of points when smoothing the residual differences” indicating point cloud points subjected to smoothing [analogous to the recited smoothing process] for reconstruction and data compression, correction values are being used for the smoothing process, which the correction values here are values of the point cloud points, Par. [0311] discloses “attribute correction values for the attributes of the points”; Therefore, the correction values of the points are analogous to the recited correction target point; therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of a target correction point representing attributes of the point cloud points being subject to a smoothing process as a result of reconstruction and compression, moreover, Par. [0061] discloses “each point in the point cloud shown may have one or more attributes associated with the point. Note that point cloud is shown in 2D…but may include points in 3D space” hence, the attributes are in 2D as well. Thus in order to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality [paragraph 0307 of Mammou]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi in view of OH in combination of an information processing device with a the circuitry is configured to correct two-dimensional coordinates of the boundary point as the boundary correction process, and correct two-dimensional coordinates of the point as the smoothing process. Moreover, Joshi’s point that is subjected to the smoothing process can be modified to be corrected with attribute correction values representing the attributes of the points, in 2D information as well, before being subject to the smoothing process as taught in Mammou.
Such a modification is the result of combing prior art elements. Joshi, OH and Mammou share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing device comprising circuitry configured to obtain reference point from a point cloud data, set the reference point on a basis of geometry of the boundary vertex subjected to a boundary correction process, wherein the circuitry is configured to set a correction target point to be subjected to the smoothing process and a correction utilization point to be used in the smoothing process on a basis of the set reference point to correct two-dimensional coordinates of the correction target point as the smoothing process.. Thus in order to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality with the correction performed on the attributes of the point cloud points, in 2D information as well, before being subjected to the smoothing process [paragraph 0307 of Mammou].
Regarding claim 6, Joshi in view of OH in combination explicitly teaches the information processing device according to claim 1, wherein Joshi explicitly teaches
the circuitry is further configured to (Par. [0010] discloses the process of the invention to be executed by a processor)
execute, on a basis of position correction coordinate information including information regarding a position point to be corrected (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process] such as discussed, Par. [0050] discloses “boundary points to be smoothed” indicating the boundary points are being set as reference for the correction process; moreover, Par. [0044] discloses “stores the groups of points as patches on a 2D frames…to encode the geometry information…based on a location (U,V) of a pixel in the geometry frame corresponds to a (X,Y,X) location of a point in 3D space” indicating the geometry information being in 2D coordinate, therefore, the geometry smoothing of the points of the point cloud is a smoothing process on 2D coordinates of the points; and the “location (U,V)” is analogous to the recited “on a basis of position correction coordinate information”) and a geometry after correction (Par. [0143] discloses “find the smoothed geometry for each boundary point. The smoothing engine determines whether the distance between a single boundary point and the filter output is larger than a threshold….when the distance between a single boundary point and the filter output is less than the threshold, the smoothing engine determines that no geometry smoothing is necessary for the boundary point” indicating that the geometry smoothing is based on a filter output, being smoothing geometry for each boundary point; therefore, the filter output is analogous to the recited “geometry after correction”), a position correction process to correct a geometry of the position point (Par. [0230] discloses “the decoder derives the centroid for each identified boundary cells. Smoothing is performed, for a boundary point based on the identified centroids of the boundary cells that are associated with that particular boundary point”, moreover, Par. [0231] discloses “the decoder generates a second lookup table that includes the centroid values of the boundary cells. The decoder modifies the predetermined entry values of the boundary cells that are included in the first lookup table to generate a correspondence between the boundary cells of the first lookup table and the boundary cells of the second lookup table” the modification of the lookup table is analogous to a position correction process, since it’s to modify the value position information of the centroid points being associated with the boundary points, and the modified information is being used to perform the smoothing process, which as discussed, is to correction the geometry of the position correction target point [points in the point cloud]), wherein and
set the reference point on a basis of the position correction coordinate information (Par. [0044] discloses “stores the groups of points as patches on a 2D frames…to encode the geometry information…based on a location (U,V) of a pixel in the geometry frame corresponds to a (X,Y,X) location of a point in 3D space” indicating the geometry information being in 2D coordinate, therefore, the geometry smoothing of the points of the point cloud is a smoothing process on 2D coordinates of the points; and the “location (U,V)” is analogous to the recited “on a basis of position correction coordinate information”, which indicates the setting of the reference point is based on the position correction coordinate information).
However, Joshi in view of OH in combination is silent on the position point being a correction target point.
In the same field of point cloud smoothing (Title and Abstract, Mammou), Mammou explicitly teaches the position point being a correction target point (Par. [0307] discloses “a balance may be reaches between quality of a reconstructed point cloud and efficiency, wherein more quantization increases compression efficiency and less quantization creases quality…an update operator may smooth residual differences, e.g. predicted attribute values that are used to determine attribute correction values, in order to increase compression efficiency while taking into account relative influence or important of points when smoothing the residual differences” indicating point cloud points subjected to smoothing [analogous to the recited smoothing process] for reconstruction and data compression, correction values are being used for the smoothing process, which the correction values here are values of the point cloud points, Par. [0311] discloses “attribute correction values for the attributes of the points”; therefore, the correction values of the points are analogous to the recited correction target point, moreover, Par. [0061] discloses “each point in the point cloud shown may have one or more attributes associated with the point. Note that point cloud is shown in 2D…but may include points in 3D space” hence, the attributes are in 2D as well; Therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of a target correction point representing attributes of the point cloud points being subject to a smoothing process as a result of reconstruction and compression. Thus in order to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality [paragraph 0307 of Mammou]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi in view of OH in combination of an information processing device with a circuitry is further configured to execute, on a basis of position correction coordinate information including information regarding a position point to be corrected and a geometry after correction, a position correction process to correct a geometry of the position point. Moreover, Joshi’s point that is subjected to the smoothing process can be modified to be corrected with attribute correction values representing the attributes of the points, in 2D information as well, before being subject to the smoothing process as taught in Mammou.
Such a modification is the result of combing prior art elements. Joshi, OH and Mammou share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing device comprising circuitry configured to obtain reference point from a point cloud data, set the reference point on a basis of geometry of the boundary vertex subjected to a boundary correction process, wherein the circuitry is configured to execute, on a basis of position correction coordinate information including information regarding a position correction target point to be corrected and a geometry after correction, a position correction process to correct a geometry of the position correction target point, and set the reference point on a basis of the position correction coordinate information. The motivation for the proposed modification would have been to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality with the correction performed on the attributes of the point cloud points, in 2D information as well, before being subjected to the smoothing process (paragraph [0307] of Mammou).
Regarding claim 7, Joshi in view of OH and Mammou in combination explicitly teaches the information processing device according to claim 6, wherein Joshi explicitly teaches
the circuitry is configured to (Par. [0010] discloses the process of the invention to be executed by a processor)
set the boundary point subjected to the boundary correction process (Par. [0050] discloses “boundary points to be smoothed” indicating the boundary points are being set as reference for the correction process; moreover, Par. [0211] discloses “each of the points have an (x,y) location…the point is a boundary point…the boundary point is located on the bottom left corner of the cell” therefore, indicating the boundary point is a corner point, which is analogous to the recited boundary vertex to be performed to boundary correction process on as discussed, therefore, the boundary points being boundary vertex [corner point] as the reference for the correction process) and the position correction process as the reference point (Par. [0230] discloses “the decoder derives the centroid for each identified boundary cells. Smoothing is performed, for a boundary point based on the identified centroids of the boundary cells that are associated with that particular boundary point”, moreover, Par. [0231] discloses “the decoder generates a second lookup table that includes the centroid values of the boundary cells. The decoder modifies the predetermined entry values of the boundary cells that are included in the first lookup table to generate a correspondence between the boundary cells of the first lookup table and the boundary cells of the second lookup table” the modification of the lookup table is analogous to a position correction process, since it’s to modify the value position information of the centroid points being associated with the boundary points, and the modified information is being used to perform the smoothing process, which as discussed, is to correction the geometry of the position correction target point [points in the point cloud], therefore, the boundary point being set as reference point for the correction process, is also based on the values being modified for the centroid associated with the boundary points, hence, it can be understood that the setting of the reference point is for a position correction process).
However, Joshi is silent on the boundary point being a boundary vertex.
In the same field of transmitting and processing point cloud data as bitstream (Abstract, OH), OH explicitly teaches the boundary point being a boundary vertex (Par. [0101] discloses “the elements of the point cloud content providing system illustrated in FIG. 1 may be implemented by…a processor” being analogous to the circuitry; moreover, Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B; furthermore, Par. [0105] discloses “the point cloud data may include the geometry and attributes of a point” indicating that the vertex also has geometry such as claimed. Therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of the vertex to represent the corner point of a block voxel structure to then be for further processing such as setting the boundary vertex subjected to the boundary correction process. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices [Par. 0003 of OH]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi of a device to correct two-dimensional coordinates of a boundary point as a boundary correction process, and correct two-dimensional coordinates of a correction target point as a smoothing process. Moreover, Joshi’s boundary point can be modified to be rendered and represented as vertex with geometry information being rendered representative point of a point cloud as taught in OH.
Such a modification is the result of combing prior art elements. Joshi and OH share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing device comprising circuitry configured to decode a bitstream obtained by dividing a mesh that represents an object with a three-dimensional structure into at least a first patch and a second patch, placing the first patch and the second patch within a single image, and encoding the single image; execute a boundary correction process to correct a geometry for a boundary vertex located at a boundary of the patches decoded; and set the boundary vertex subjected to the boundary correction process as a reference point and executes a smoothing process to smooth a geometry for a vertex within a partial area based on the reference point. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices, see Par. [0003] of OH, to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH.
Regarding claim 8, Joshi in view of OH and Mammou in combination explicitly teaches the information processing device according to claim 6, wherein Joshi explicitly teaches
the circuitry is configured to (Par. [0010] discloses the process of the invention to be executed by a processor)
set an in-patch point (Paragraph [0050] discloses “to perform both attribute and geometry smoothing…methods of identifying points of the reconstructed 2D point cloud that are represented by pixels in the frames at or near a patch boundary…certain cells that either include a boundary point or that are in proximity to a boundary point…denoted as boundary cells….the decoder derives a centroid of the boundary cells which are used to determine…point needs to be smoothed” therefore, indicating that the boundary point being subject to smoothing can be at or near the patch boundary, in the instances where it’s being near the patch boundary, it is analogous to in-patch vertex as claimed), located inside the patch and subjected to the position correction process (as discussed, being near the boundary is being located in the patch and subjected to the position correction process; Par. [0230] discloses “the decoder derives the centroid for each identified boundary cells. Smoothing is performed, for a boundary point based on the identified centroids of the boundary cells that are associated with that particular boundary point”, moreover, Par. [0231] discloses “the decoder generates a second lookup table that includes the centroid values of the boundary cells. The decoder modifies the predetermined entry values of the boundary cells that are included in the first lookup table to generate a correspondence between the boundary cells of the first lookup table and the boundary cells of the second lookup table” the modification of the lookup table is analogous to a position correction process, since it’s to modify the value position information of the centroid points being associated with the boundary points, and the modified information is being used to perform the smoothing process, which as discussed, is to correction the geometry of the position correction target point [points in the point cloud], therefore, the boundary point being set as reference point for the correction process, is also based on the values being modified for the centroid associated with the boundary points, hence, it can be understood that the setting of the reference point is for a position correction process), as the reference point (therefore, the boundary point being set as reference point for the correction process, is also based on the values being modified for the centroid associated with the boundary points, hence, it can be understood that the setting of the reference point is for a position correction process.
However, Joshi is silent on a process to set an in-patch vertex as the reference point.
In the same field of transmitting and processing point cloud data as bitstream (Abstract, OH), OH explicitly teaches to set an in-patch vertex as the reference point (Par. [0101] discloses “the elements of the point cloud content providing system illustrated in FIG. 1 may be implemented by…a processor” being analogous to the circuitry; moreover, Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B; furthermore, Par. [0105] discloses “the point cloud data may include the geometry and attributes of a point” indicating that the vertex also has geometry such as claimed. Therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of the vertex to represent the corner point of a block voxel structure to then be for further processing such as setting an in-patch vertex as a reference point. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices [Par. 0003 of OH]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi of a device to set an in-patch point, located inside a patch and subjected to a position correction process, as a reference point. Moreover, Joshi’s boundary point can be modified to be rendered and represented as vertex with geometry information being rendered representative point of a point cloud as taught in OH.
Such a modification is the result of combing prior art elements. Joshi and OH share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing device comprising circuitry configured to decode a bitstream obtained by dividing a mesh that represents an object with a three-dimensional structure into at least a first patch and a second patch, placing the first patch and the second patch within a single image, and encoding the single image; execute a boundary correction process to correct a geometry for a boundary vertex located at a boundary of the patches decoded; and set the boundary vertex subjected to the boundary correction process as a reference point and executes a smoothing process to smooth a geometry for a vertex within a partial area based on the reference point; and set an in-patch vertex, located inside the patch and subjected to the position correction process, as the reference point. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices, see Par. [0003] of OH, to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH, and further to correct the point cloud element based on adjusting quality of the point cloud content by the method discussed, see OH’s Par. [0119].
Regarding claim 11, Joshi in view of OH in combination explicitly teaches the information processing device according to claim 9, wherein Joshi explicitly teaches
the circuitry is configured to (Par. [0010] discloses the process of the invention to be executed by a processor)
set a point to be subjected to the smoothing process (Par. [0050] discloses “geometry smoothing…the boundary points can be smoothed to remove the visual artifact and thereby increasing the visual appearance of the point cloud…boundary points to be smoothed…by deriving the centroid for only the boundary cells” indicating it’s being used to perform the smoothing of the boundary points [utilization for correction], the point cloud here is being processed for the smoothing to increase visual appearance, therefore, any point within the point cloud is being analogous to the point as claimed for a geometry smoothing process) and a correction utilization point to be used in the smoothing process (Par. [0050] discloses “geometry smoothing…the boundary points can be smoothed to remove the visual artifact and thereby increasing the visual appearance of the point cloud…boundary points to be smoothed…by deriving the centroid for only the boundary cells” indicating the boundary points are being set as reference for the correction process, the centroid here is analogous to the recited correction utilization point) on a basis of the smoothing information (Par. [0050] discloses “geometry smoothing…the boundary points can be smoothed to remove the visual artifact and thereby increasing the visual appearance of the point cloud…boundary points to be smoothed…by deriving the centroid for only the boundary cells” indicating the boundary points are being set as reference for the correction process, the centroid here is analogous to the recited correction utilization point, since it’s being used to perform the smoothing of the boundary points [utilization for correction], the point cloud here is being processed for the smoothing to increase visual appearance, therefore, any point within the point cloud is being analogous to the correction target point as claimed for a geometry smoothing process; moreover, Par. [0103] discloses “the encoder transmits frames representing the point cloud as an encoded bitstream” to be processed by the decoder, this transmitted information is required for the smoothing process, hence, is analogous to the smoothing information as claimed being acquired by the decoder).
However, Joshi in view of OH in combination is silent on a process to set a correction target point to be subjected to the smoothing process.
In the same field of point cloud smoothing (Title and Abstract, Mammou), Mammou explicitly teaches to set a correction target point to be subjected to the smoothing process (Par. [0307] discloses “a balance may be reaches between quality of a reconstructed point cloud and efficiency, wherein more quantization increases compression efficiency and less quantization creases quality…an update operator may smooth residual differences, e.g. predicted attribute values that are used to determine attribute correction values, in order to increase compression efficiency while taking into account relative influence or important of points when smoothing the residual differences” indicating point cloud points subjected to smoothing [analogous to the recited smoothing process] for reconstruction and data compression, correction values are being used for the smoothing process, which the correction values here are values of the point cloud points, Par. [0311] discloses “attribute correction values for the attributes of the points”; therefore, the correction values of the points are analogous to the recited correction target point; therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of a target correction point representing attributes of the point cloud points being subject to a smoothing process as a result of reconstruction and compression. Thus in order to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality [paragraph 0307 of Mammou]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi in view of OH in combination of a processing device with a circuitry is configured to set a point to be subjected to the smoothing process and a correction utilization point to be used in the smoothing process on a basis of the set reference point as taught in Joshi. Moreover, Joshi’s point that is subjected to the smoothing process can be modified to be corrected with attribute correction values representing the attributes of the points before being subject to the smoothing process as taught in Mammou.
Such a modification is the result of combing prior art elements. Joshi, OH and Mammou share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing device comprising circuitry configured to obtain reference point from a point cloud data, set the reference point on a basis of geometry of the boundary vertex subjected to a boundary correction process, wherein the circuitry is configured to set a correction target point to be subjected to the smoothing process and a correction utilization point to be used in the smoothing process on a basis of the set reference point. Thus in order to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality (paragraph [0307] of Mammou).
Regarding claim 12, Joshi in view of OH in combination explicitly teaches the information processing device according to claim 9, wherein Joshi explicitly teaches
the circuitry is configured to (Par. [0010] discloses the process of the invention to be executed by a processor)
correct a geometry of a point to be subjected to the smoothing process (Par. [0050] discloses “geometry smoothing…the boundary points can be smoothed to remove the visual artifact and thereby increasing the visual appearance of the point cloud…boundary points to be smoothed…by deriving the centroid for only the boundary cells” indicating it’s being used to perform the smoothing of the boundary points [utilization for correction], the point cloud here is being processed for the smoothing to increase visual appearance, therefore, any point within the point cloud is being analogous to the correction target point as claimed for a geometry smoothing process) by a method indicated by the smoothing information (Par. [0050] discloses “geometry smoothing…the boundary points can be smoothed to remove the visual artifact and thereby increasing the visual appearance of the point cloud…boundary points to be smoothed…by deriving the centroid for only the boundary cells” indicating the boundary points are being set as reference for the correction process, the centroid here is analogous to the recited correction utilization point, since it’s being used to perform the smoothing of the boundary points [utilization for correction], the point cloud here is being processed for the smoothing to increase visual appearance, therefore, any point within the point cloud is being analogous to the correction target point as claimed for a geometry smoothing process; moreover, Par. [0103] discloses “the encoder transmits frames representing the point cloud as an encoded bitstream” to be processed by the decoder, this transmitted information is required for the smoothing process, hence, is analogous to the smoothing information as claimed being acquired by the decoder).
However, Joshi in view of OH in combination is silent on a process to correct a geometry of a correction target point to be subjected to the smoothing process.
In the same field of point cloud smoothing (Title and Abstract, Mammou), Mammou explicitly teaches to correct a geometry of a correction target point to be subjected to the smoothing process (Par. [0307] discloses “a balance may be reaches between quality of a reconstructed point cloud and efficiency, wherein more quantization increases compression efficiency and less quantization creases quality…an update operator may smooth residual differences, e.g. predicted attribute values that are used to determine attribute correction values, in order to increase compression efficiency while taking into account relative influence or important of points when smoothing the residual differences” indicating point cloud points subjected to smoothing [analogous to the recited smoothing process] for reconstruction and data compression, correction values are being used for the smoothing process, which the correction values here are values of the point cloud points, Par. [0311] discloses “attribute correction values for the attributes of the points” also indicating that the correction values are values of the attributes of the points in 3D space with coordinates including geometry, Par. [0173] discloses “locations of points in 3D space, such as X, Y, and Z coordinates of the points”; therefore, the correction values of the points are analogous to the recited correction target point representing the points in 3D space with 3D coordinates; therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of a target correction point representing attributes of the point cloud points being subject to a smoothing process of its 3D coordinate data, as a result of reconstruction and compression. Thus in order to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality [paragraph 0307 of Mammou]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi in view of OH in combination of an information processing device with a circuitry is configured to correct three-dimensional coordinates, including geometry, of the point as the smoothing process as taught by Joshi. Moreover, Joshi’s point that is subjected to the smoothing process, on its 3D coordinate data, can be modified to be corrected with attribute correction values representing the attributes of the points before being subject to the smoothing process as taught in Mammou.
Such a modification is the result of combing prior art elements. Joshi, OH and Mammou share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing device comprising circuitry configured to obtain reference point from a point cloud data, set the reference point on a basis of geometry of the boundary vertex subjected to a boundary correction process, wherein the circuitry is configured to set a correction target point to be subjected to the smoothing process and a correction utilization point to be used in the smoothing process on a basis of the set reference point to correct a geometry of a correction target point to be subjected to the smoothing process. Thus in order to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality (paragraph [0307] of Mammou).
Regarding claim 16, Joshi in view of OH in combination explicitly teaches the information processing device according to claim 14, wherein Joshi explicitly teaches
the smoothing information includes information (Par. [0050] discloses “geometry smoothing…the boundary points can be smoothed to remove the visual artifact and thereby increasing the visual appearance of the point cloud…boundary points to be smoothed…by deriving the centroid for only the boundary cells” indicating the boundary points are being set as reference for the correction process, the centroid here is analogous to the recited correction utilization point, since it’s being used to perform the smoothing of the boundary points [utilization for correction], the point cloud here is being processed for the smoothing to increase visual appearance, therefore, any point within the point cloud is being analogous to the correction target point as claimed for a geometry smoothing process) for specifying a point serving as a point to be subjected to the smoothing process (Par. [0048] discloses “smoothing the points of the 3D point cloud….a patch boundary” indicating smoothing of boundary [correction process] such as discussed, Par. [0050] discloses “boundary points to be smoothed” indicating the boundary points are being set as reference for the correction process; moreover, Par. [0044] discloses “stores the groups of points as patches on a 2D frames…to encode the geometry information…based on a location (U,V) of a pixel in the geometry frame corresponds to a (X,Y,X) location of a point in 3D space” indicating the geometry information being in 2D coordinate, therefore, the geometry smoothing of the points of the point cloud is a smoothing process on 2D coordinates of the points; and the “location (U,V)” is analogous to the recited “on a basis of position correction coordinate information”; and the 3D point cloud as discussed including the boundary point in point cloud as well, hence, can be understood as the vertex serving as correction target point as claimed) and a vertex serving as a correction utilization point to be used in the smoothing process (Par. [0230] discloses “the decoder derives the centroid for each identified boundary cells. Smoothing is performed, for a boundary point based on the identified centroids of the boundary cells that are associated with that particular boundary point”, moreover, Par. [0231] discloses “the decoder generates a second lookup table that includes the centroid values of the boundary cells. The decoder modifies the predetermined entry values of the boundary cells that are included in the first lookup table to generate a correspondence between the boundary cells of the first lookup table and the boundary cells of the second lookup table” the modification of the lookup table is analogous to a position correction process, since it’s to modify the value position information of the centroid points being associated with the boundary points, and the modified information is being used to perform the smoothing process, which as discussed, is to correction the geometry of the position correction target point [points in the point cloud]; since the centroid is based on the boundary point being associated with each other, it can be understood that the vertex serving as information for the correction utilization point).
However, Joshi is silent on specifying a vertex serving as a correction target point to be subjected to the smoothing process.
In the same field of transmitting and processing point cloud data as bitstream (Abstract, OH), OH explicitly teaches specifying a vertex serving as a correction target point to be subjected to the smoothing process (Par. [0101] discloses “the elements of the point cloud content providing system illustrated in FIG. 1 may be implemented by…a processor” being analogous to the circuitry; moreover, Par. [0152] discloses “a vertex present along an edge is detected when there is at least one occupied voxel adjacent to the edge among all blocks sharing the edge” such as shown in Figure 5, Par. [0142] discloses “FIG. 5 shows an example of voxels generated through an octree structure” which shows the voxel structure that is similar to Joshi’s Figure 7B; furthermore, Par. [0105] discloses “the point cloud data may include the geometry and attributes of a point” indicating that the vertex also has geometry such as claimed. Therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of the vertex to represent the corner point of a block voxel structure to then be for further processing such as specifying a point serving as a correction target point to be subjected to the smoothing process. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices [Par. 0003 of OH]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi of a device to perform specifying a point serving as a correction target point to be subjected to the smoothing process. Moreover, Joshi’s boundary point can be modified to be rendered and represented as vertex with geometry information being rendered representative point of a point cloud as taught in OH.
Such a modification is the result of combing prior art elements. Joshi and OH share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing device comprising circuitry configured perform specifying a vertex serving as a correction target point to be subjected to a smoothing process and a vertex serving as a correction utilization point to be used in the smoothing process. Thus in order to have the point cloud content to be represented in an efficient processing of large amount of point data by having it represented and rendered as vertices, see Par. [0003] of OH, to ensure better image quality in region that need to be focused processing on by at a reduce processing load, see Par. [0344] of OH.
However, Joshi in view of OH in combination is silent on specifying a vertex serving as a correction target point to be subjected to the smoothing process.
In the same field of point cloud smoothing (Title and Abstract, Mammou), Mammou explicitly teaches specifying a vertex serving as a correction target point to be subjected to the smoothing process (Par. [0307] discloses “a balance may be reaches between quality of a reconstructed point cloud and efficiency, wherein more quantization increases compression efficiency and less quantization creases quality…an update operator may smooth residual differences, e.g. predicted attribute values that are used to determine attribute correction values, in order to increase compression efficiency while taking into account relative influence or important of points when smoothing the residual differences” indicating point cloud points subjected to smoothing [analogous to the recited smoothing process] for reconstruction and data compression, correction values are being used for the smoothing process, which the correction values here are values of the point cloud points, Par. [0311] discloses “attribute correction values for the attributes of the points”; therefore, the correction values of the points are analogous to the recited correction target point; therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of a target correction point representing attributes of the point cloud points being subject to a smoothing process as a result of reconstruction and compression, moreover, Par. [0061] discloses “each point in the point cloud shown may have one or more attributes associated with the point. Note that point cloud is shown in 2D…but may include points in 3D space” hence, the attributes are in 2D as well. Thus in order to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality [paragraph 0307 of Mammou]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi in view of OH in combination of an information processing device to have smoothing information includes information for specifying a point serving as a point to be subjected to the smoothing process and a vertex serving as a correction utilization point to be used in the smoothing process. Moreover, Joshi’s point that is subjected to the smoothing process can be modified to be corrected with attribute correction values representing the attributes of the points before being subject to the smoothing process as taught in Mammou.
Such a modification is the result of combing prior art elements. Joshi, OH and Mammou share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing device comprising circuitry configured perform specifying a vertex serving as a correction target point to be subjected to a smoothing process. Thus in order to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality with the correction performed on the attributes of the point cloud points, in 2D information as well, before being subjected to the smoothing process [paragraph 0307 of Mammou].
Regarding claim 17, Joshi in view of OH in combination explicitly teaches the information processing device according to claim 14, wherein Joshi explicitly teaches the smoothing information includes information indicating (Par. [0050] discloses “geometry smoothing…the boundary points can be smoothed to remove the visual artifact and thereby increasing the visual appearance of the point cloud…boundary points to be smoothed…by deriving the centroid for only the boundary cells” indicating it’s being used to perform the smoothing of the boundary points [utilization for correction], the point cloud here is being processed for the smoothing to increase visual appearance, therefore, any point within the point cloud is being analogous to the correction target point as claimed for a geometry smoothing process) a method of correcting a geometry of a point to be subjected to the smoothing process (Par. [0050] discloses “geometry smoothing…the boundary points can be smoothed to remove the visual artifact and thereby increasing the visual appearance of the point cloud…boundary points to be smoothed…by deriving the centroid for only the boundary cells” indicating the boundary points are being set as reference for the correction process, the centroid here is analogous to the recited correction utilization point, since it’s being used to perform the smoothing of the boundary points [utilization for correction], the point cloud here is being processed for the smoothing to increase visual appearance, therefore, any point within the point cloud is being analogous to the correction target point as claimed for a geometry smoothing process; moreover, Par. [0103] discloses “the encoder transmits frames representing the point cloud as an encoded bitstream” to be processed by the decoder, this transmitted information is required for the smoothing process, hence, is analogous to the smoothing information as claimed being acquired by the decoder).
However, Joshi in view of OH in combination is silent on a method of correcting a geometry of a correction target point to be subjected to the smoothing process.
In the same field of point cloud smoothing (Title and Abstract, Mammou), Mammou explicitly teaches a method of correcting a geometry of a correction target point to be subjected to the smoothing process (Par. [0307] discloses “a balance may be reaches between quality of a reconstructed point cloud and efficiency, wherein more quantization increases compression efficiency and less quantization creases quality…an update operator may smooth residual differences, e.g. predicted attribute values that are used to determine attribute correction values, in order to increase compression efficiency while taking into account relative influence or important of points when smoothing the residual differences” indicating point cloud points subjected to smoothing [analogous to the recited smoothing process] for reconstruction and data compression, correction values are being used for the smoothing process, which the correction values here are values of the point cloud points, Par. [0311] discloses “attribute correction values for the attributes of the points”; therefore, the correction values of the points are analogous to the recited correction target point; therefore, it would have been obvious to one of ordinary skill of the art at the time the invention was made to have the use of a target correction point representing attributes of the point cloud points being subject to a smoothing process as a result of reconstruction and compression, moreover, Par. [0061] discloses “each point in the point cloud shown may have one or more attributes associated with the point. Note that point cloud is shown in 2D…but may include points in 3D space” hence, the attributes are in 2D as well. Thus in order to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality [paragraph 0307 of Mammou]).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing data of the claimed invention was made to combine the teachings of Joshi in view of OH in combination of an information processing device to have the smoothing information includes information indicating a method of correcting a geometry of a point to be subjected to the smoothing process. Moreover, Joshi’s point that is subjected to the smoothing process can be modified to be corrected with attribute correction values representing the attributes of the points before being subject to the smoothing process as taught in Mammou.
Such a modification is the result of combing prior art elements. Joshi, OH and Mammou share the same field of endeavor of point cloud processing. The motivation for the proposed modification would have been to have an information processing device, wherein a smoothing information includes information indicating a method of correcting a geometry of a correction target point to be subjected to the smoothing process. Thus in order to have quantization of the point cloud data with efficiency in compression and at the same time with compression quality with the correction performed on the attributes of the point cloud points, in 2D information as well, before being subjected to the smoothing process [paragraph 0307 of Mammou].
Pertinent Prior Art(s)
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Chao Huang et. al., “US 2023/0074762 A1,” discloses a mesh coding method to decode bitstream carrying 3D mesh frame includes a plurality of patches, the process involves determining connectivity information of a subset of vertices to then reconstruct the patches of the 3D mesh frame based on a portion of attributes and the connectivity information (abstract).
Nobuhito Suehira et. al., “US 2012/0229763 A1” discloses an optical tomographic image photographing apparatus having a tracking function, capable of appropriately controlling a scan in acquiring a tomographic image. The optical tomographic image photographing apparatus according to the invention includes a fundus image photographing section which photographs fundus images of an eye to be inspected and a tomographic image photographing section which photographs tomographic images of the eye to be inspected. A control method of the optical tomographic image photo graphing apparatus includes the steps of calculating coordinate values matching a plurality of previously-acquired characteristic areas in the fundus image;
Conclusion
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/PHUONG HAU CAI/ Examiner, Art Unit 2673
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673
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