DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
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 of this title, 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.
Claim 1-2, 4-10, 16 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Thudor U.S. Patent Application 20200380765 in view of Westman U.S. Patent Application 20240242369.
Regarding claim 20, Thudor discloses an apparatus comprising:
a processor (microprocessor 122); and
a memory (ROM 123) storing instructions operative, when executed by the processor, to cause the apparatus to:
obtain a slicing parameter; obtain a target point cloud geometry; partition the target point cloud, wherein partitioning the target point cloud comprises applying the slicing parameter and a set of partition parameters to the target point cloud (paragraph [0118]: the point cloud and its partitioning are represented in 2D, according to θ and φ only. The 3D parts resulting from the partitioning are illustrated with squares 5100, 5110, 51mn arranged in a matrix fashion, wherein ‘m’ corresponds to the row index and ‘n’ corresponds to the column index; paragraph [0109]: one or more maps comprising information representative of the geometry of the scene, e.g. depth maps, are determined... A depth-based segmentation algorithm may then be performed to segment the scene according to the geometry information);
partition another point cloud, wherein partitioning the other point cloud comprises applying the slicing parameter and the set of partition parameters to the other point cloud (paragraph [0117]: the partitioning of the point cloud may vary from a GOP (Group of Pictures) to another GOP; paragraph [0138]: The partitioning of the object 5 may vary over time, for example from a GOP to another following GOP, or when a change in the topology of the object 5 has been changed or every q frames, with q an integer greater than or equal to 1. Such a variation in the partitioning is illustrated in FIG. 5 with the frame j; paragraph [0118]: the point cloud and its partitioning are represented in 2D, according to θ and φ only. The 3D parts resulting from the partitioning are illustrated with squares 5100, 5110, 51mn arranged in a matrix fashion, wherein ‘m’ corresponds to the row index and ‘n’ corresponds to the column index);
for each partition of the target point cloud: process a GPU-based recoloring function with the corresponding partition of the point cloud to generate one or more partitioned and recolored point clouds (paragraph [0247]: encoding/decoding data representative of a 3D scene but also extends to a method for generating a bitstream comprising the encoded data and to any device implementing this method and notably any devices comprising at least one CPU and/or at least one GPU; paragraph [0081]: A depth map (also called height map) and a texture map (also called color map) are determined for and associated with each part of the 3D representation using the one or more parameters describing the 2D parameterization associated with each part; paragraph [0240]: operation 162, the data representative of at least a texture map associated with the at least a part of the 3D representation is decoded from the bitstream);
assemble the one or more partitioned and recolored point clouds; and output the one or more assembled point clouds (paragraph [0242]: the data associated with at least a point comprised in the at least a part of said 3D representation is determined from the at least a parameter, the data representative of the texture map(s), the data representative of the depth map(s),… and a second information obtained/decoded from the bitstream and representative of a mapping between the 2D parameterization(s) and corresponding depth and texture maps; paragraph [0243]: The decoded data and information may further be used to generate/reconstruct a 3D representation of the 3D scene for the rendering and/or displaying of the reconstructed 3D scene).
Thudor discloses all the features with respect to claim 20 as outlined above. However, Thudor fails to disclose obtaining a reference point cloud geometry with attribute, partition the reference point cloud.
Westman discloses s obtaining a reference point cloud geometry with attribute (paragraph [0055]: the first and second sets of features to be extracted are local descriptors that provide geometric information about their respective point clouds and assist with generating effective correspondences between the query point cloud and the reference point cloud),
partition the reference point cloud (paragraph [0052]: downsampling the query point cloud and the reference point cloud may include the localization module partitioning both point clouds into grids of equally-spaced and non-overlapping voxels (i.e., small three-dimensional boxes));
for each partition of the target point cloud: process a GPU-based function (paragraph [0073]: The GPU may have a parallel structure that is efficient for parallel processing of large blocks of data);
assemble the one or more partitioned a point clouds (paragraph [0059]: Block 412 of method 400 may include determining a coarse alignment based on the plurality of matches between the first set of features from the query point cloud and the second set of features from the reference point cloud).
Therefore, it would have been obvious before the effective filing date of the claimed invention to combine Thudor’s to segment reference point cloud as taught by Westman, to determine viewpoint position and orientation relative to an HD map.
Claim 1 recites the functions of the apparatus recited in claim 20 as method steps. Accordingly, the mapping of the prior art to the corresponding functions of the apparatus in claim 20 applies to the method steps of claim 1.
Regarding claim 2, Thudor as modified by Westman discloses the method of claim 1, further comprising generating the set of partition parameters (Thudor’s paragraph [0118]: the point cloud and its partitioning are represented in 2D, according to θ and φ only. The 3D parts resulting from the partitioning are illustrated with squares 5100, 5110, 51mn arranged in a matrix fashion, wherein ‘m’ corresponds to the row index and ‘n’ corresponds to the column index).
Therefore, it would have been obvious before the effective filing date of the claimed invention to combine Thudor’s to segment reference point cloud as taught by Westman, to determine viewpoint position and orientation relative to an HD map.
Regarding claim 4, Thudor as modified by Westman discloses the method of claim 1, wherein obtaining the slicing parameter comprises decoding the slicing parameter (Thudor’s paragraph [0239]: In a first operation 161, at least a parameter representative of at least a two-dimensional parameterization of at least a part of the 3D representation is decoded from a received bitstream; paragraph [0139]: A first patch atlas 63 is generated from the first partitioning 61, the first patch atlas 63 comprising the depth maps obtained from the 2D parameterizations associated with the 3D parts resulting from the partitioning 61).
Therefore, it would have been obvious before the effective filing date of the claimed invention to combine Thudor’s to segment reference point cloud as taught by Westman, to determine viewpoint position and orientation relative to an HD map.
Regarding claim 5, Thudor as modified by Westman discloses the method of claim 1, wherein obtaining the slicing parameter comprises obtaining a bitstream, and wherein the bitstream comprises the slicing parameter (Thudor’s paragraph [0239]: In a first operation 161, at least a parameter representative of at least a two-dimensional parameterization of at least a part of the 3D representation is decoded from a received bitstream; paragraph [0139]: A first patch atlas 63 is generated from the first partitioning 61, the first patch atlas 63 comprising the depth maps obtained from the 2D parameterizations associated with the 3D parts resulting from the partitioning 61).
Therefore, it would have been obvious before the effective filing date of the claimed invention to combine Thudor’s to segment reference point cloud as taught by Westman, to determine viewpoint position and orientation relative to an HD map.
Regarding claim 6, Thudor as modified by Westman discloses the method of claim 1, wherein the target point cloud geometry comprises at least one of:
a predicted point cloud geometry of a current frame, a reconstructed point cloud geometry of the current frame, and an input point cloud geometry of the current frame (Thudor’s paragraph [0184]: The decoded point cloud 903 may then be further processed for reconstructing the 3D representation of the scene from the decoded pictures that comprise the attributes (depth and texture), from the decoded density information, from the decoded parameters representative of the 2D parameterizations and from the decoded mapping information for the mapping between the 2D parameterizations and the depth and texture maps comprised in the decoded pictures; paragraph [0109]: one or more maps comprising information representative of the geometry of the scene, e.g. depth maps, are determined).
Therefore, it would have been obvious before the effective filing date of the claimed invention to combine Thudor’s to segment reference point cloud as taught by Westman, to determine viewpoint position and orientation relative to an HD map.
Regarding claim 7, Thudor as modified by Westman discloses the method of claim 1, further comprising applying the one or more assembled point clouds to a predictive attribute decoder (Thudor’s paragraph [0168]: The operation 104 comprises for example the generation of predictors for inter prediction for the coding of one or more pictures of the point cloud, different from the picture 100 (e.g. pictures of the point cloud at determined times different from the time ‘t’ of picture 100). The point cloud 901, or pictures representing the point cloud, may then be encoded by referring to the reference picture 103. According to a variant, the module M104 is part of the encoder ENC1; see fig. 10).
Therefore, it would have been obvious before the effective filing date of the claimed invention to combine Thudor’s to segment reference point cloud as taught by Westman, to determine viewpoint position and orientation relative to an HD map.
Regarding claim 8, Thudor as modified by Westman discloses the method of claim 1, further comprising: applying the one or more assembled point clouds to a predictive attribute encoder; and encoding the slicing parameters into a bitstream (Thudor’s paragraph [0168]: The operation 104 comprises for example the generation of predictors for inter prediction for the coding of one or more pictures of the point cloud, different from the picture 100 (e.g. pictures of the point cloud at determined times different from the time ‘t’ of picture 100). The point cloud 901, or pictures representing the point cloud, may then be encoded by referring to the reference picture 103. According to a variant, the module M104 is part of the encoder ENC1; see fig. 10).
Therefore, it would have been obvious before the effective filing date of the claimed invention to combine Thudor’s to segment reference point cloud as taught by Westman, to determine viewpoint position and orientation relative to an HD map.
Regarding claim 9, Thudor as modified by Westman discloses the method of claim 1, wherein processing, for each partition of the target point cloud, the GPU-based recoloring function with the corresponding partition of the reference point cloud comprises:
splitting the GPU-based recoloring function into a series of split GPU-based recoloring functions corresponding respectively to the partitions of the reference point cloud; and generating a partitioned and recolored point cloud for each partition of the target point cloud (Thudor’s paragraph [0247]: encoding/decoding data representative of a 3D scene but also extends to a method for generating a bitstream comprising the encoded data and to any device implementing this method and notably any devices comprising at least one CPU and/or at least one GPU; paragraph [0081]: A depth map (also called height map) and a texture map (also called color map) are determined for and associated with each part of the 3D representation using the one or more parameters describing the 2D parameterization associated with each part; paragraph [0240]: operation 162, the data representative of at least a texture map associated with the at least a part of the 3D representation is decoded from the bitstream; Westman’s paragraph [0073]: The GPU may have a parallel structure that is efficient for parallel processing of large blocks of data).
Therefore, it would have been obvious before the effective filing date of the claimed invention to combine Thudor’s to segment reference point cloud as taught by Westman, to determine viewpoint position and orientation relative to an HD map.
Regarding claim 10, Thudor as modified by Westman discloses the method of claim 1, wherein partitioning the reference point cloud comprises:
inputting the reference point cloud, the slicing parameter, and the set of partition parameters into a partitioning process; and partitioning the reference point cloud into a set of partitioned reference point clouds, wherein the slicing parameter indicates quantity of partitioned reference point clouds (Thudor’s paragraph [0118]: the point cloud and its partitioning are represented in 2D, according to θ and φ only. The 3D parts resulting from the partitioning are illustrated with squares 5100, 5110, 51mn arranged in a matrix fashion, wherein ‘m’ corresponds to the row index and ‘n’ corresponds to the column index; Westman’s paragraph [0055]: the first and second sets of features to be extracted are local descriptors that provide geometric information about their respective point clouds and assist with generating effective correspondences between the query point cloud and the reference point cloud).
Therefore, it would have been obvious before the effective filing date of the claimed invention to combine Thudor’s to segment reference point cloud as taught by Westman, to determine viewpoint position and orientation relative to an HD map.
Regarding claim 16, Thudor as modified by Westman discloses the method of claim 1, wherein the slicing parameter is an integer equal to 0, 1, 2, or 3 (Thudor’s paragraph [0144]: The point cloud representing the object 5 is partitioned into a plurality of 3D parts; paragraph [0123]: a first patch atlas 53 according to a determined or random arrangement, for example in a matrix fashion with rows and columns; see fig. 5 first patch atlas 53 has 3 rows/slices).
Therefore, it would have been obvious before the effective filing date of the claimed invention to combine Thudor’s to segment reference point cloud as taught by Westman, to determine viewpoint position and orientation relative to an HD map.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Thudor U.S. Patent Application 20200380765 in view of Westman U.S. Patent Application 20240242369, and further in view of Jung U.S. Patent Application 20170353722.
Regarding claim 3, Thudor as modified by Westman discloses partitioning the reference point cloud (Westman's paragraph [0052]: downsampling the query point cloud and the reference point cloud may include the localization module partitioning both point clouds into grids of equally-spaced and non-overlapping voxels (i.e., small three-dimensional boxes)). However, Thudor as modified by Westman fails to disclose partitioning the reference point cloud is performed before partitioning the target point cloud.
Jung discloses partitioning the reference point cloud is performed before partitioning the target point cloud (paragraph [0022]: the textural similarities which exist between the current block of the current image and the zone pointed to in the reference image, to optimize the partitioning of the current block; Jung’s teaching of partitioning reference image to guide partitioning of current image can be combined with Thudor and Westman’s device, such that to partition reference point cloud to guide partition target point cloud).
Therefore, it would have been obvious before the effective filing date of the claimed invention to combine Thudor and Westman’s to partition reference image first as taught by Jung, to adapt finely to the shapes and the textures of the objects in the image.
Allowable Subject Matter
Claim 11-15 and 17-19 are 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 and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
Claim 11 is about computing variance of geometry of the target point cloud; selecting boundary axes for the target point cloud using the computed variance; estimating boundaries for the target point cloud based on the selected boundary axes; and partitioning the target point cloud based on the estimated boundaries.
Thudor 20200380765, Westman 20240242369, Schroeder 20100292963 and Tourapis 20250054197 combined cannot teach these features perfectly. These limitations when read in light of the rest of the limitations in the claim and the claims to which it depends make the claim allowable subject matter.
Claim 12-15 depends on claim 11, are allowed based on same reason as claim 11.
Claim 17 is about performing a first GPU-based nearest neighbor search from the reference point cloud to the target point cloud; performing a second GPU-based nearest neighbor search from the target point cloud to the reference point cloud; and performing a distance-based weighted attribute interpolation using nearest neighbor lists generated by the first and second GPU-based nearest neighbor searches.
Thudor 20200380765, Westman 20240242369, Tourapis 20250054197 and Yea 20200304829 combined cannot teach these features perfectly. These limitations when read in light of the rest of the limitations in the claim and the claims to which it depends make the claim allowable subject matter.
Claim 18-19 depends on claim 17, are allowed based on same reason as claim 17.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Yi Yang whose telephone number is (571)272-9589. The examiner can normally be reached on Monday-Friday 9:00 AM-6:00 PM EST.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Daniel Hajnik can be reached on 571-272-7642. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/YI YANG/
Primary Examiner, Art Unit 2616
Prosecution Insights