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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 06/29/2026 has been entered.
Applicant(s) Response to Official Action
The response filed on 06/29/2026 has been entered and made of record.
Response to Arguments/Amendments
Presented arguments have been fully considered but are held unpersuasive. Examiner’s response to the presented arguments follows below.
Claim Rejections - 35 USC § 103
Summary of Arguments:
Regarding claims 1 & 14, the Applicant argues:
“Mammou does not disclose a decompression system which obtains a geometry-based point cloud coding (G-PCC) compressed three-dimensional point cloud.” “The system of Mammou obtains one or more encoded image frames of a compressed point cloud (so 2D compressed data), decodes these and generates a decompressed version of the compressed (3D) point cloud.” [Remarks: Page 7]
“On the contrary, the claimed invention relates to using geometry-based point cloud compression (G-PCC) and decompression for (de)compressing multiple arrays of 2D data.” “So, in the claimed invention, the starting point (before compressing) and end result (after decompressing) of the claims is a plurality of 2D arrays while geometry-based point cloud compression (3D) is used.” [Remarks: Page 7]
“Substituting G-PCC for Mammou’s approach would fundamentally change the operation of the system and defeat the purpose of Mammou’s projection-based encoding.” “Combining Mammou with any other reference can never lead to a decompression system obtaining a G-PCC compressed three-dimensional point cloud.” [Remarks: Page 7]
Regarding claims 2-6, 8-10, 17-18, 21-23, the Applicant argues:
The claims “depend from claim 1 or claim 14, are patentable for at least the same reasons.” [Remarks: Page 7]
Regarding claims 19-20, the Applicant argues:
The “Sinharoy does not cure the deficiencies of Mammou and Sugio noted above. Therefore, claims 19-20 are patentable over the cited combination.” [Remarks: Page 8]
Examiner’s Response:
Regarding claims 1 & 14, the Examiner contends:
This argument fails because a rejection under 35 U.S.C. § 103 relies on the combined teachings of multiple references, not the strict disclosures of the primary reference alone. While Mammou (US 2021/0150766 A1) utilizes a 2D projection-based compression method, replacing this with a geometry-based compression method represents a simple substitution of one known point cloud compression standard for another. A Person Having Ordinary Skill in the Art (PHOSITA) would find it obvious to use G-PCC techniques, such as the voxel-based hierarchical spaces taught by Sugio (US 2021/0368186 A1), to achieve the same overall goal of point cloud compression.
This argument is unpersuasive because the claim itself is directed specifically to a “decompression system”, meaning the limitations are evaluated based on the structural steps executed during decompression, regardless of the original data's state before encoding. The claim explicitly recites obtaining a compressed 3D point cloud, decompressing it into a 3D point cloud, and then converting it to 2D arrays. Mammou discloses the structural concept of mapping between 3D point cloud coordinate data and 2D arrays. A PHOSITA would recognize that the mapping techniques utilized in Mammou can be adapted for the post-decompression step of organizing the 3D data back into 2D arrays for subsequent temporal tracking or display processing.
This argument fails because incorporating G-PCC does not defeat the fundamental purpose of Mammou, which is to efficiently store and transmit point cloud data. Sugio provides a robust framework for geometry-based volume and voxel encoding. A PHOSITA would be motivated to substitute or combine Mammou's specific 2D video codec approach with the geometry-based 3D approach of Sugio to optimize the system for volumetric rendering or specific hardware requirements. Combining these known compression architectures yields the predictable result of a decoded point cloud mapped to a 2D array, which aligns with standard obviousness rationales.
Regarding claims 2-6, 8-10, 17-18, 21-23, the Examiner contends:
The argument is moot based on the response above regarding claims 1 & 14.
Regarding claims 19-20, the Examiner contends:
The argument is moot based on the response above regarding claims 1 & 14.
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.
Claims 1-6, 8-10, 14, 17-18, 21-23 are rejected under 35 U.S.C. 103 as being unpatentable over Mammou et al., hereinafter referred to as Mammou (US 2021/0150766 A1) in view of Sugio (US 2021/0368186 A1).
As per claim 1, Mammou discloses a decompression system (Mammou: Abstract.) comprising at least one processor the at least one processor being configured to (Mammou: Paras. [0010], [0016] disclose a decompression system comprising at least one processor the at least one processor being configured to:):
obtain (Mammou: Para. [0010] discloses receiving one or more encoded image frames of a compressed point cloud.),
decompress the (Mammou: Paras. [0011]-[0012], [0103] disclose decoding the one or more encoded image frames and generating a decompressed version of the compressed point cloud based, at least in part, on the determined spatial information for the plurality of patches and the attribute and geometry information included in the patches [i.e., the system decompresses the point cloud using geometry and spatial information].), and
convert the three-dimensional point cloud to a plurality of two-dimensional arrays of element values by dividing the three-dimensional point cloud into a plurality of three-dimensional subspaces (Mammou: Para. [0306] discloses “project point cloud data/patches … on a 4:4:4 grid” and Para. [0134] discloses “projecting the points belonging to each patch” [i.e., converting the point cloud into 2D array grids by dividing the 3D geometry into patches for projection]), selecting a corresponding three-dimensional subspace for each position in the two-dimensional arrays (Mammou: Para. [0136] discloses “Let H(u, v) be the set of points of the current patch that get projected to the same pixel (u,v)” [i.e., selecting a projection ray or subspace H(u,v) that corresponds to each pixel position in the 2D array].), and determining an element value for each position in the two-dimensional arrays based on one or more values of one or more data points in the corresponding three-dimensional subspace (Mammou: Paras. [0136]-[0141], [0175] disclose determining an element value (e.g., depth, texture, or attribute) for each pixel position in the 2D array by evaluating the 3D data points within the projection ray/subspace H(u, v) corresponding to that pixel, and assigning the pixel based on the associate point, or an average/linear combination if multiple data points occupy that subspace.),
However, Mammou does not explicitly disclose “… a geometry-based point cloud coding (G-PCC) … decompress the G-PCC compressed three-dimensional point cloud into a three-dimensional point cloud by applying geometry-based point cloud decompression to the G-PCC compressed three-dimensional point cloud … same positions in each of the plurality of two-dimensional arrays comprising a value of a same element at a different moment.”.
Further, Sugio is in the same field of endeavor and teaches “obtain[ing] a geometry-based point cloud coding (G-PCC)” and “decompress[ing] the G-PCC compressed three-dimensional point cloud into a three-dimensional point cloud by applying geometry-based point cloud decompression to the G-PCC compressed three-dimensional point cloud” (Sugio: Para. [0880] discloses “First decoder 5340 reproduces point cloud data by decoding encoded data (encoded stream) [claimed decompress the G-PCC compressed three-dimensional point cloud into a three-dimensional point cloud by applying geometry-based point cloud decompression to the G-PCC compressed three-dimensional point cloud] generated by encoding the point cloud data in the first encoding method (GPCC) [claimed obtain a geometry-based point cloud coding (G-PCC) compressed three-dimensional point cloud]”.).
same positions in each of the plurality of two-dimensional arrays comprising a value of the same element at a different moment (Sugio: Para. [0207] discloses “temporal prediction in which a prediction unit corresponding to a different time is referred to,” Sugio: Para. [0569] discloses “encodes (inter predicts) a space (SPC) associated with certain time T_Cur using an encoded space associated with different time T_LX,” and Sugio: Para. [0237] discloses “the same dynamic object is encoded as an object in a GOS corresponding to a different time” [i.e., utilizing temporal prediction across frames such that the same spatial elements or objects are tracked across prediction units at different moments in time].).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, and having the teachings of Mammou and Sugio before him or her, to modify the point cloud data processing system of Mammou to include the G-PCC volumetric decompression and same positions in two-dimensional arrays comprising a value of the same element at a different moment feature as described in Sugio. The motivation for doing so would have been to improve spatial-to-temporal point cloud compression by providing a highly structured configuration that efficiently organizes 3D data and tracks temporal changes of identical spatial elements across sequential moments in time.
As per claim 2, Mammou-Sugio disclose the decompression system as claimed in claim 1, wherein the two-dimensional arrays of element values are frames comprising pixel values (Sugio: Paras. [0216], [0556]-[0557] disclose three-dimensional data included in the VLM subspace includes, for example, at least one pair of a spatial position such as three-dimensional coordinates and an attribute value such as color information [includes pixel values], which is mapped to two-dimensional arrays.).
As per claim 3, Mammou-Sugio disclose the decompression system as claimed in claim 1, wherein the element values comprise values derived from at least one sensor (Sugio: Para. [0458] discloses a plurality of sensors 815 are a group of sensors, such as visible light cameras and infrared cameras, that obtain information on the outside of the vehicle and generate sensor information 833. Sensor information 833 is, for example, three-dimensional data such as a point cloud (point group data), when sensors 815 are laser sensors such as LiDARs. Note that a single sensor may serve as a plurality of sensors 815.).
As per claim 4, Mammou-Sugio disclose the decompression system as claimed in claim 3, wherein the element values comprise color values (Sugio: Paras. [0216], [0556]-[0557] disclose three-dimensional data included in the VLM subspace includes, for example, at least one pair of a spatial position such as three-dimensional coordinates and an attribute value such as color information, which is mapped to two-dimensional arrays.).
As per claim 5, Mammou-Sugio disclose the decompression system as claimed in claim 1, wherein the at least one processor is configured to obtain metadata indicating dimensions of the plurality of two-dimensional arrays and divide the three-dimensional point cloud into the plurality of three-dimensional subspaces based on the indicated dimensions (Mammou: Para. [0105] discloses “metadata associated with patches … patch information indicating sizes and shapes of patches” and Para. [0245] discloses “extent of its 2D bounding box (DU0, DV0)” [i.e., metadata indicates the dimensions (sizes/bounding boxes) of the 2D arrays (patches), which controls how the point cloud is divided into subspaces for projection.).
As per claim 6, Mammou-Sugio-Kim disclose the decompression system as claimed in claim 5, wherein the at least one processor is configured to determine point cloud dimensions of the three-dimensional point cloud and divide the three-dimensional point cloud into a plurality of three-dimensional subspaces further based on the determined point cloud dimensions (Mammou: Paras. [0244]-[0246] disclose “Minimum/maximum/average/median depth value” [i.e., the metadata defines the point cloud dimensions via minimum/maximum depths, which is used to divide the subspaces]).
As per claim 8, Mammou-Sugio disclose the decompression system as claimed in claim 1, wherein the G-PCC compressed three-dimensional point cloud was compressed using lossy geometry-based point cloud compression and the at least one processor is configured to determine for each position in the two-dimensional arrays whether the corresponding three-dimensional subspace comprises at least one data point and if a three-dimensional subspace corresponding to a position in the two-dimensional arrays does not comprise a data point, determine a geometrical shape encompassing the three-dimensional subspace and determine an element value for the position based on one or more element values of one or more data points which are part of the determined geometrical shape. (Mammou: Para. [0152] discloses “lossy compression”, Para. [0134] discloses “If H(u, v) is empty then the pixel is marked as unoccupied”, and Para. [0186] discloses “padding may be performed to fill the non-occupied pixels … For each block … the intra prediction modes … are assessed and the one that produces the lowest prediction errors on the occupied pixels is retained” [i.e., for empty subspaces lacking a data point, padding determines a geometric block (shape) encompassing the space and determines the pixel value based on occupied adjacent pixels].).
As per claim 9, Mammou-Sugio disclose the decompression system as claimed in claim 1, wherein the at least one processor is configured to obtain metadata identifying a method which was used to map positions of element values in an original plurality of arrays to coordinates of the data points of the three-dimensional point cloud before the three-dimensional point cloud was compressed and select the corresponding three-dimensional subspace for each position in the two-dimensional arrays based on the identified method (Mammou: Paras. [0244]-[0247] disclose before the three-dimensional point cloud was compressed, an “Index of the projection direction” is metadata that identifies the projection direction (method) used to map 3D coordinates to 2D arrays, which dictates the selection of the corresponding subspace for each position.).
As per claim 10, Mammou-Sugio disclose the decompression system as claimed in claim 1, wherein the decompression system is a terminal (Mammou: Para. [0092] discloses the decoder is implemented within an end-user terminal device such as a head-mounted display.).
As per claim 14, Mammou discloses a method of decompressing compressed two-dimensional arrays of element values (Mammou: Abstract.), the method comprising:
obtaining a (Mammou: Para. [0010] discloses receiving one or more encoded image frames of a compressed point cloud.);
decompressing the (Mammou: Paras. [0011]-[0012], [0103] disclose decoding the one or more encoded image frames and generating a decompressed version of the compressed point cloud based, at least in part, on the determined spatial information for the plurality of patches and the attribute and geometry information included in the patches [i.e., the system decompresses the point cloud using geometry and spatial information].); and
converting the three-dimensional point cloud to a plurality of two-dimensional arrays of element values by dividing the three-dimensional point cloud into a plurality of three-dimensional subspaces (Mammou: Para. [0306] discloses “project point cloud data/patches … on a 4:4:4 grid” and Para. [0134] discloses “projecting the points belonging to each patch” [i.e., converting the point cloud into 2D array grids by dividing the 3D geometry into patches for projection]), selecting a corresponding three-dimensional subspace for each position in the two-dimensional arrays (Mammou: Para. [0136] discloses “Let H(u, v) be the set of points of the current patch that get projected to the same pixel (u,v)” [i.e., selecting a projection ray or subspace H(u,v) that corresponds to each pixel position in the 2D array].), and determining an element value for each position in the two-dimensional arrays based on one or more values of one or more data points in the corresponding three-dimensional subspace (Mammou: Paras. [0136]-[0141], [0175] disclose determining an element value (e.g., depth, texture, or attribute) for each pixel position in the 2D array by evaluating the 3D data points within the projection ray/subspace H(u, v) corresponding to that pixel, and assigning the pixel based on the associate point, or an average/linear combination if multiple data points occupy that subspace.),
However, Mammou does not explicitly disclose “… a geometry-based point cloud coding (G-PCC) … decompress the G-PCC compressed three-dimensional point cloud into a three-dimensional point cloud by applying geometry-based point cloud decompression to the G-PCC compressed three-dimensional point cloud … same positions in each of the plurality of two-dimensional arrays comprising a value of a same element at a different moment.”.
Further, Sugio is in the same field of endeavor and teaches “obtain[ing] a geometry-based point cloud coding (G-PCC)” and “decompress[ing] the G-PCC compressed three-dimensional point cloud into a three-dimensional point cloud by applying geometry-based point cloud decompression to the G-PCC compressed three-dimensional point cloud” (Sugio: Para. [0880] discloses “First decoder 5340 reproduces point cloud data by decoding encoded data (encoded stream) [claimed decompress the G-PCC compressed three-dimensional point cloud into a three-dimensional point cloud by applying geometry-based point cloud decompression to the G-PCC compressed three-dimensional point cloud] generated by encoding the point cloud data in the first encoding method (GPCC) [claimed obtain a geometry-based point cloud coding (G-PCC) compressed three-dimensional point cloud]”.).
same positions in each of the plurality of two-dimensional arrays comprising a value of the same element at a different moment (Sugio: Para. [0207] discloses “temporal prediction in which a prediction unit corresponding to a different time is referred to,” Para. [0569] discloses “encodes (inter predicts) a space (SPC) associated with certain time T_Cur using an encoded space associated with different time T_LX,” and Para. [0237] discloses “the same dynamic object is encoded as an object in a GOS corresponding to a different time” [i.e., utilizing temporal prediction across frames such that the same spatial elements or objects are tracked across prediction units at different moments in time].).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, and having the teachings of Mammou and Sugio before him or her, to modify the point cloud data processing system of Mammou to include the G-PCC volumetric decompression and same positions in two-dimensional arrays comprising a value of the same element at a different moment feature as described in Sugio. The motivation for doing so would have been to improve spatial-to-temporal point cloud compression by providing a highly structured configuration that efficiently organizes 3D data and tracks temporal changes of identical spatial elements across sequential moments in time.
As per claim 17, Mammou-Sugio disclose a computer program product for a computing device, stored on a non-transitory computer-readable medium, the computer program product comprising computer program code to perform the method of claim 14 when the computer program product is run on a processing unit of the computing device.
As per claim 18, Mammou-Sugio disclose the decompression system as claimed in claim 1, wherein the element values comprise color values from a camera (Mammou: Paras. [0093]-[0094] disclose element values comprise color values from a camera.).
As per claim 21, Mammou-Sugio disclose the decompression system as claimed in claim 1, wherein the decompression system is a set-top box (Mammou: Para. [0637] discloses wherein the decompression system is a set-top box.).
As per claim 22, Mammou-Sugio disclose the decompression system as claimed in claim 1, wherein the decompression system is a computer (Mammou: Para. [0637] discloses wherein the decompression system is a computer.).
As per claim 23, Mammou-Sugio disclose the decompression system as claimed in claim 9, wherein the mapping method identifies a coordinate system used in the mapping (Mammou: Para. [0093] discloses wherein the mapping method identifies a coordinate system used in the mapping.).
Claims 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Mammou et al., hereinafter referred to as Mammou in view of Sugio in further view of Sinharoy et al., hereinafter referred to as Sinharoy (US 2019/0197739 A1).
As per claim 19, Mammou-Sugio disclose the decompression system as claimed in claim 3 (Mammou: Abstract.),
However, Mammou-Sugio do not explicitly disclose “… wherein the at least one sensor is a temperature sensor.”.
Further, Sinharoy is in the same field of endeavor and teaches wherein the at least one sensor is a temperature sensor (Sinharoy: Para. [0054] discloses wherein the at least one sensor is a temperature sensor.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, and having the teachings of Mammou-Sugio and Sinharoy before him or her, to modify the decompression system of Mammou-Sugio to include the temperature sensor feature as described in Sinharoy. The motivation for doing so would have been to improve user experience by providing an expanded configuration that can host a variety of different components that are associated with three-dimensional content.
As per claim 20, Mammou-Sugio disclose the decompression system as claimed in claim 3 (Mammou: Abstract.),
However, Mammou-Sugio do not explicitly disclose “… wherein the at least one sensor is a humidity sensor.”.
Further, Sinharoy is in the same field of endeavor and teaches wherein the at least one sensor is a humidity sensor (Sinharoy: Para. [0054] discloses wherein the at least one sensor is a humidity sensor.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, and having the teachings of Mammou-Sugio and Sinharoy before him or her, to modify the decompression system of Mammou-Sugio to include the temperature sensor feature as described in Sinharoy. The motivation for doing so would have been to improve user experience by providing an expanded configuration that can host a variety of different components that are associated with three-dimensional content.
Allowable Subject Matter
Claims 7 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure and can be viewed in the list of references.
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/PEET DHILLON/Primary Examiner
Art Unit: 2488
Date: 07-10-2026
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