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 .
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1-12, 14-18, and 20 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Zhao et al. (U.S. PGPUB 20190370989).
With respect to claim 1, Zhao et al. one or more processors (paragraph 86, processor 520 configured to execute the instructions stored in the memory 510), comprising: circuitry (paragraph 86, The apparatus 500 of FIG. 5 includes a memory 510 configured to store instructions and a processor 520 configured to execute the instructions stored in the memory 510, such hardware implies circuitry) to: generate a data structure comprising a mapping of one or more voxel coordinates to one or more corresponding points of one or more point clouds (paragraph 45, paragraph 48, paragraph 51, step 242 may include searching for a storage space of the first voxel in the target storage space according to the first voxel and pre-stored mapping relationship information, where the mapping relationship information can be used for indicating correspondences between stored voxels and storage spaces of the stored voxels); and
generate one or more voxel representations of the one or more point clouds based, at least in part, on use of the mapping to identify features of the corresponding points of the one or more point clouds (paragraph 20, the embodiments of the present disclosure provide a 3D point cloud reconstruction method based on voxels to generate a dense 3D point cloud, paragraph 29, voxels may be used as points in a 3D point cloud, and a high accuracy dense 3D point cloud may be reconstructed).
With respect to claim 2, Zhao et al. disclose the one or more processors of claim 1, wherein the circuitry is to generate the data structure to comprise one or more hash tables that store the one or more voxel coordinates as keys and one or more indications of one or more voxels of the one or more voxel representations as one or more corresponding values (paragraph 55, the mapping relationship information may be stored in a hash table, paragraph 56, the hash table may record a correspondence between position information of stored voxel blocks and storage spaces of the stored voxel blocks).
With respect to claim 3, Zhao et al. disclose the one or more processors of claim 1, wherein the circuitry is to generate the one or more data structures using an amount of memory based, at least in part, on a number of point locations in the one or more point clouds (paragraph 62, The target storage spaces may be located in a memory of a graphics processing unit (GPU), or may be located in a memory of a central processing unit (CPU), or may even be located in an external storage device, paragraph 66, in a 3D point cloud map reconstruction, the embodiments of the present disclosure may include using the CPU memory to store a reconstructed global map, using the GPU memory to store a local map).
With respect to claim 4, Zhao et al. disclose the one or more processors of claim 1, wherein the circuitry is to use the data structure to access one or more data values, and to generate one or more feature values of one or more voxels of the one or more voxel representations based, at least in part, on the one or more data values (paragraph 79, the hash table may record the correspondence between the position information of the stored voxel block and the storage space of the stored voxel block. A voxel block may include a plurality of spatially adjacent voxels, and position information of the stored voxel block may be used to indicate a spatial position of the stored voxel block in a 3D scene).
With respect to claim 5, Zhao et al. disclose the one or more processors of claim 1, wherein the circuitry is to store one or more data values indicative of features associated with the corresponding points within one or more memory locations to be accessed based, at least in part, on data stored in the data structure (paragraph 24, The memory 190 may store all or portions of the input feature data associated with each 3D point in the 3D pointcloud data set 110. The compute engine may store in memory 190 the intermediate results 194 from processing the pointcloud data (e.g. on a tile or level basis), which may be used in subsequent data fetches for other levels, tiles, etc.).
With respect to claim 6, Zhao et al. disclose the one or more processors of claim 1, wherein the circuitry is to iterate over the one or more voxel coordinates to generate, using the data structure, one or more feature values of one or more voxels of the one or more voxel representations (paragraph 56, The above-described searching for the storage space of the first voxel in the target storage space through the hash algorithm, according to the first voxel and the hash table, may include determining position information of a target voxel block that the first voxel belongs to; searching for a storage space of the target voxel block through the hash algorithm, according to the position information of the target voxel block and the hash table; and according to a position of the first voxel in the target voxel block, searching for the storage space of the first voxel in the storage space of the target voxel block).
With respect to claim 7, Zhao et al. disclose the one or more processors of claim 1, wherein the circuitry is to input one or more indications of the one or voxel coordinates into a hash function to output one or more indications of one or more voxels of the one or more voxel representations (paragraph 56, The above-described searching for the storage space of the first voxel in the target storage space through the hash algorithm, according to the first voxel and the hash table, may include determining position information of a target voxel block that the first voxel belongs to; searching for a storage space of the target voxel block through the hash algorithm, according to the position information of the target voxel block and the hash table; and according to a position of the first voxel in the target voxel block, searching for the storage space of the first voxel in the storage space of the target voxel block).
With respect to claim 8, Zhao et al. disclose a system (paragraph 86, FIG. 5 is a schematic structural diagram of an apparatus for 3D point cloud reconstruction), comprising: one or more processors (paragraph 86, The apparatus 500 of FIG. 5 includes a memory 510 configured to store instructions and a processor 520) as in claim 1; see rationale for rejection of claim 1.
With respect to claim 9, Zhao et al. disclose the system of claim 8, wherein the one or more processors are to generate the data structure to comprise one or more hash tables based, at least in part, on one or more arrays of the one or more voxel coordinates and one or more arrays of one or more indications of one or more voxels of the one or more voxel representations (paragraph 59, The hash table in the embodiments of the present disclosure may be designed in order to quickly and efficiently find a voxel block in an array. A hash table entry can contain a position of the voxel block, a pointer pointing to an array that stores the voxel block, an offset, or another member variable).
With respect to claim 10, Zhao et al. disclose the system of claim 8, wherein the one or more processors are to generate the data structure using an amount of memory that is at least twice a number of one or more point locations in the one or more point clouds (paragraph 60, the hash table may record the above-described mapping relationship information using the following data structure: where pos[3] can represent world coordinates (x, y, z) of the voxel block in the 3D space, pointer can point to a starting address of an array storing the voxel block, offset can be used to indicate an offset between a starting address of a storage position of the voxel block and the starting address of the array storing the voxel block). The data structure comprises twice the data (point and offset) to a voxel location.
With respect to claim 11, Zhao et al. disclose the system of claim 8, wherein the one or more processors are to generate the data structure to comprise one or more tables to index one or more voxels of the one or more voxel representations as a function of the one or more voxel coordinates (paragraph 56, The above-described searching for the storage space of the first voxel in the target storage space through the hash algorithm, according to the first voxel and the hash table, may include determining position information of a target voxel block that the first voxel belongs to; searching for a storage space of the target voxel block through the hash algorithm, according to the position information of the target voxel block and the hash table; and according to a position of the first voxel in the target voxel block, searching for the storage space of the first voxel in the storage space of the target voxel block). The hash algorithm corresponds to a function.
With respect to claim 12, Zhao et al. disclose the system of claim 8, wherein the one or more processors are to indicate one or more voxels of the one or more voxel representations based, at least in part, on one or more indications of memory locations used to store one or more indications of one or more voxels of the one or more voxel representations (paragraph 60, pointer can point to a starting address of an array storing the voxel block, offset can be used to indicate an offset between a starting address of a storage position of the voxel block and the starting address of the array storing the voxel block).
With respect to claim 14, Zhao et al. disclose the system of claim 8, wherein the one or more processors are to input one or more indications of the one or more voxel coordinates into a hash function to output one or more indications of one or more memory locations used to store one or more indications of one or more voxels of the one or more voxel representations (paragraph 55, The above-described searching for the storage space of the first voxel in the target storage space according to the first voxel and the pre-stored mapping relationship information may include, according to the first voxel and a hash table, through a hash algorithm, searching for the storage space of the first voxel in the target storage space, paragraph 59, A hash table entry can contain a position of the voxel block, a pointer pointing to an array that stores the voxel block, an offset, or another member variable).
With respect to claim 15, Zhao et al. disclose a method as executed by the system of claim 1; see rationale for rejection of claim 1.
With respect to claim 16, Zhao et al. disclose the method of claim 15, further comprising generating the data structure to comprise one or more hash tables using the one or more voxel coordinates as keys to indicate one or more voxels of the one or more voxel representations to be generated (paragraph 55, the mapping relationship information may be stored in a hash table, paragraph 56, the hash table may record a correspondence between position information of stored voxel blocks and storage spaces of the stored voxel blocks).
With respect to claim 17, Zhao et al. disclose the method of claim 15, further comprising generating the data structure to use an amount of memory based, at least in part, on a number of points in the one or more point clouds (paragraph 62, The target storage spaces may be located in a memory of a graphics processing unit (GPU), or may be located in a memory of a central processing unit (CPU), or may even be located in an external storage device, paragraph 66, in a 3D point cloud map reconstruction, the embodiments of the present disclosure may include using the CPU memory to store a reconstructed global map, using the GPU memory to store a local map).
With respect to claim 18, Zhao et al. disclose the method of claim 15, further comprising accessing one or more indications of memory locations used to store one or more indications of one or more voxels of the one or more voxel representations (paragraph 60, pointer can point to a starting address of an array storing the voxel block, offset can be used to indicate an offset between a starting address of a storage position of the voxel block and the starting address of the array storing the voxel block).
With respect to claim 20, Zhao et al. disclose the method of claim 15, further comprising using the data structure to access one or more data values, and to generate one or more voxels based, at least in part, on the one or more data values (paragraph 79, the hash table may record the correspondence between the position information of the stored voxel block and the storage space of the stored voxel block. A voxel block may include a plurality of spatially adjacent voxels, and position information of the stored voxel block may be used to indicate a spatial position of the stored voxel block in a 3D scene).
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.
Claim(s) 13 and 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhao et al. (U.S. PGPUB 20190370989) in view of Oh et al. (U.S. PGPUB 20220159312).
With respect to claim 13, Zhao et al. disclose the system of claim 8, wherein the one or more processors are to iterate over the one or more voxel coordinates to: identify, using the data structure, a number of corresponding points mapped to a coordinate of the one or more voxel coordinates (paragraph 56, The above-described searching for the storage space of the first voxel in the target storage space through the hash algorithm, according to the first voxel and the hash table, may include determining position information of a target voxel block that the first voxel belongs to; searching for a storage space of the target voxel block through the hash algorithm, according to the position information of the target voxel block and the hash table; and according to a position of the first voxel in the target voxel block, searching for the storage space of the first voxel in the storage space of the target voxel block). However, Zhao et al. do not expressly disclose generating, using the identified number of corresponding points, one or more mean feature values of a voxel of the one or more voxel representations, the voxel corresponding to the coordinate.
Oh et al., who also deal with 3D data, disclose a method for generating, using the identified number of corresponding points, one or more mean feature values of a voxel of the one or more voxel representations, the voxel corresponding to the coordinate. (paragraph 299, the attribute transformation unit 40007 according to the embodiments performs attribute transformation related thereto. In one embodiment, the attribute transformation unit 40007 may adjust the attribute value of the voxel to the average value of the color or reflectance of points included in the voxel or the average value of the color or reflectance of neighboring points within a specific radius from the position value of the center point of the voxel).
Zhao et al. and Oh et al. are in the same field of endeavor, namely computer graphics.
Before the effective filing date of the claimed invention, it would have been obvious to apply the method of generating, using the identified number of corresponding points, one or more mean feature values of a voxel of the one or more voxel representations, the voxel corresponding to the coordinate, as taught by Oh et al., to the Zhao et al. system, because redundant information between the pieces of attribute information may be reduced (paragraph 305 of Oh et al.).
With respect to claim 19, Zhao et al. as modified by Oh et al. disclose the method of claim 15, further comprising iterating over the one or more voxel coordinates to generate, using the data structure, one or more sum feature values of one or more voxels of the one or more voxel representations (Oh et al.: paragraph 362, the geometry reconstruction unit 11003 directly invokes and adds the position information value of the point). It would have been obvious to perform iterating over the one or more voxel coordinates to generate, using the data structure, one or more sum feature values of one or more voxels of the one or more voxel representations because this would implement positions decoded and output by the geometry decoder and point cloud content including attribute information decoded and output by the attribute decoder are output to the renderer 10007 paragraph 376 of Oh et al.).
Response to Arguments
Applicant’s arguments with respect to claim(s) 1, 8, and 15 have been considered but are moot in view of the new ground(s) of rejection.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
U.S. PGPUB 20240062466 to Schur et al. for a method of converting a point cloud into a voxel grid
U.S. PGPUB 20210192689 to Bosse et al. for a method of converting point clouds to voxel space
U.S. PGPUB 20190385355 to Xu for a method of using a voxel hashing algorithm.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANDREW GUS YANG whose telephone number is (571)272-5514. The examiner can normally be reached M-F 9 AM - 5:30 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kent Chang can be reached at (571)272-7667. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ANDREW G YANG/Primary Examiner, Art Unit 2614
1/27/26