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 .
Response to Arguments
Applicant’s arguments, see page 9, filed 04/13/2026, with respect to claim 17 have been fully considered and are persuasive. The minor objection of 01/13/2026 has been withdrawn.
Applicant’s arguments, see page 9, filed 04/13/2026, with respect to claims 1-19 have been fully considered and are persuasive. The 35 USC 112(b) rejection of 01/13/2026 has been withdrawn.
Applicant's arguments filed 04/13/2026 have been fully considered but they are not persuasive. See the below arguments regarding the 35 USC 103 rejection of claims 1-7 and 10-20.
Applicant argues:
“As can be seen from the above, Tourapis is directed to adjusting spatial images, texture images, or other attribute images to compensate for geometric distortion and to determining updated spatial information for points associated with a patch. Tourapis does not teach or suggest performing quality enhancement on attribute data of converted two-dimensional pictures in the manner recited in the pending claims, nor does Tourapis disclose the claimed operations or relationships among representative points, nearest neighboring points, and attribute data as required by the claims.
In other words, Tourapis adjusts spatial images, texture images, and/or other attribute images to correct for geometric distortion and updates spatial information accordingly. This disclosure concerns compensating for geometry-related distortion, not subjecting attribute data of converted two-dimensional pictures to quality enhancement as expressly required by the amended claims.
Moreover, Tourapis discloses updating spatial information of points, rather than updating attribute data of a point cloud based on attribute data of two-dimensional pictures after quality enhancement, as also required by the pending claims. For example, claim 1 requires that quality enhancement be performed on attribute data of the converted two-dimensional pictures and that the attribute data of the point cloud be updated according to the attribute data of the two-dimensional pictures after quality enhancement-features that are neither taught nor suggested by Tourapis.
Thus, Tourapis fails to teach or suggest the above-emphasized features of claim 1, or the corresponding features of independent claims 11 and 20.”
Examiner Response: The Examiner respectfully points to FIGs. 6A-C and corresponding paragraphs ¶370-382:
Tourapis teaches converted 2D attribute data: “[0371] the process segments a point cloud frame into multiple 2D projected images/videos, each representing different types of information… This process is performed by segmenting the point cloud into multiple patches that permit one to efficiently project the 3D space data of the point cloud onto 2D planes. Each patch is associated with information such as geometry, texture, and/or other attributes… results in a collection of multiple sub streams , e.g. a geometry sub stream, texture and attribute sub streams, as well as occupancy and auxiliary information sub streams…”
Tourapis teaches quality enhancement on attribute data: “[0373-0382] One of the characteristics of this point cloud coding scheme is that the different projected image sequences can be not only compressed using "conventional ” codecs but also processed with conventional processing algorithms reserved for 2D image/video data. That is, one could apply de-noising, scaling, enhancement, and/or other algorithms commonly used for processing 2D image data onto these image sequences.”
Tourapis teaches updating the attribute data after quality enhancement: “[0679-0681, FIG. 6A] Texture Processing/Filtering (602) occurs before Point Cloud Generation (240) outputs Reconstructed Point Cloud (246). [0131] states: “In decoder 280, the video/image streams are first decoded, then an inverse motion compensation and delta prediction procedure may be applied. The obtained images are then used in order to reconstruct a point cloud, which may be smoothed as described previously (see also [0373-0382]) to generate a reconstructed point cloud 282.” [0679-0682] further discloses “wherein the one or more encoded image frames further comprise a patch image comprising attribute information for at least one of the patches, wherein the decoder is further configured to: identify the patch image comprising attribute information; and assign attribute information included in the patch image to respective ones of the points of the set of points of the at least one patch.” Thus, the post-enhanced 2D patch attribute information is used to generate/update the reconstructed point cloud by assigning the processed patch attribute information to the corresponding points.
Applicant further argues:
“Wang does not make up for the deficiencies of Tourapis. In Wang, by adding the neighboring point from a different 3D patch to one 3D patch, the problem of the crack occurred due to distortion at the intersections of the 3D patches may be solved…
In other words, Wang discloses adding the neighboring point to a 3D patch, to achieve extension of geometry of 3D patch, rather than quality enhancement of attribute of the converted 2D pictures. Despite this disclosure, Wang is completely silent as to performing any quality enhancement on attribute data of the converted 2D pictures and updating attribute data of the point cloud according to the attribute data of the 2D pictures after quality enhancement as presently claimed.
Specifically, the claims require that quality enhancement be performed on attribute data of the converted 2D pictures, and the attribute data of the point cloud is updated according to the attribute data of the 2D pictures after quality enhancement.
Thus, Wang fails to teach or suggest the above-emphasized features of claim 1, or the corresponding features of independent claims 11 and 20.”
Examiner Response:
Applicant’s argument is not persuasive because the rejection does not rely on Wang alone for the disputed limitation. The examiner respectfully points to paragraphs [0050-0058] of Wang.
Wang supports updating the attribute data of the point cloud according to the attribute data after quality enhancement: “[0051] The patch expanding module … adds a color of the neighboring point to the texture image of the patch P1…[0057] After the patches P1 to P6 added with the neighboring points are obtained, in step S409, a point cloud reconstruction module (not illustrated) may be used to reconstruct the point cloud PC according to the patches P1 to P6 so as to obtain the reconstructed point cloud PC.”
In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., relationships among representative points, nearest neighboring points, and attribute data) are not recited in rejected claims 1, 16, or 20. Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
For at least these reasons (see also the 103 rejection below), Applicant’s arguments are unpersuasive and claims 1-7 and 10-20 remain rejected under 35 USC 103.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-5, 7, 10-14, 16-17, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Tourapis (US 2022/0005228 A1), in further view of Wang (US 2020/0294270 A1).
Consider claims 1, 11, and 20, Tourapis discloses a point cloud decoding device, comprising:
at least one processor (FIG. 16 Processor #1610a-n); and
a memory coupled to the at least one processor and storing at least one computer executable instruction thereon which, when executed by the at least one processor (FIG. 16 Memory #1620, Program Instructions #1622), causes the at least one processor to:
A point cloud decoding/encoding method (FIG. 5A-5D), comprising:
decoding a point cloud bitstream to output a point cloud, the point cloud comprising attribute data and geometry data (¶347, 349; FIG. 5B #550 Decoder, #240 point cloud generation; FIG. 5D #516, 518; ¶114-115; “a captured point cloud, such as captured point cloud 110, may include spatial and attribute information for the points included in the point cloud.”);
extracting a plurality of three-dimensional (3D) patches from the point cloud (FIG. 5B #238; FIG. 5D #522; ¶120; intra-frame decoder, patches; ¶132; “A segmentation process may decompose a point cloud into a minimum number of patches (e.g., a contiguous subset of the surface described by the point cloud)” );
converting the extracted plurality of three-dimensional patches into two-dimensional (2D) pictures (FIG. 8C; ¶121, 122; “Geometry/Texture/Attribute generation” modules, such as modules 210, 212, and 214, generate 2D patch images associated with the geometry/texture/attributes”; ¶155; “The image generation process described above consists of projecting the points belonging to each patch onto its associated projection plane to generate a patch image.”; ¶358); and
performing quality enhancement on attribute data of the converted two-dimensional pictures, and updating the attribute data of the point cloud according to the attribute data of the two-dimensional pictures after quality enhancement; and (FIG. 5B, 6A, FIG. 10 #1055, 1056; ¶346, patches, reconstructed geometry image, correcting for changes in patch shape; ¶131; “The obtained images are then used in order to reconstruct a point cloud, which may be smoothed as described previously to generate a reconstructed point cloud 282”; ¶290, 373-382, ¶456, 679-682; ¶707; “determining, for the at least one patch, updated spatial information for the set of points of the at least one patch based, at least in part, on the vector motion information; and generating an updated decompressed version of the compressed point cloud based, at least in part, on the updated spatial information.”; “In decoder 280, the video/image streams are first decoded, then an inverse motion compensation and delta prediction procedure may be applied. The obtained images are then used in order to reconstruct a point cloud, which may be smoothed as described previously (see also [0373-0382]) to generate a reconstructed point cloud 282.” [0679-0682] further discloses “wherein the one or more encoded image frames further comprise a patch image comprising attribute information for at least one of the patches, wherein the decoder is further configured to: identify the patch image comprising attribute information; and assign attribute information included in the patch image to respective ones of the points of the set of points of the at least one patch.” Thus, the post-enhanced 2D patch attribute information is used to generate/update the reconstructed point cloud by assigning the processed patch attribute information to the corresponding points.)
encoding the point cloud with the updated attribute data, and outputting a point cloud bitstream (Tourapis ¶295, 346, 373-382, 679-682, FIG. 5A Encoder #500, Compressed point cloud information #204).
In related art, Wang further supports encoding the point cloud with the updated attribute data (Wang ¶51-58; “The patch expanding module … adds a color of the neighboring point to the texture image of the patch P1… After the patches P1 to P6 added with the neigh
boring points are obtained, in step S409, a point cloud reconstruction module (not illustrated) may be used to reconstruct the point cloud PC according to the patches P1 to P6 so as to obtain the reconstructed point cloud PC.”).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the processing of texture/color attributes during point cloud reconstruction of Wang into the quality enhancement of Tourapis to predictably yield a reconstructed point cloud with improved quality.
Consider claim 2, Tourapis, as modified by Wang, discloses the claimed invention wherein:
the attribute data contains a luma component (Tourapis ¶112, 294-298); and
performing quality enhancement on the attribute data of the converted two-dimensional pictures, and updating the attribute data of the point cloud according to the attribute data of the two-dimensional pictures after quality enhancement comprises (Wang ¶64, FIG. 4A; Tourapis FIG. 4C; ¶113, 294-304):
performing quality enhancement on luma components of the converted two-dimensional pictures, and updating the luma component contained in the attribute data of the point cloud according to the luma components of the two-dimensional pictures after quality enhancement (Tourapis FIG. 6A, ¶113, 294-304, 370-382; “wherein the one or more parameters are adjusted to improve quality of the final decompressed point cloud colors and to reduce the size of the compressed point cloud”; Wang FIG. 4A ¶51-58).
Consider claims 3 and 12, Tourapis, as modified by Wang, discloses the claimed invention wherein extracting the plurality of three-dimensional patches from the point cloud comprises (Tourapis ¶132-154 Segmentation Process):
determining a plurality of representative points in the point cloud (Tourapis ¶132-140);
determining a nearest neighbouring point for each of the plurality of representative points, wherein the nearest neighbouring point of one representative point denotes a set of nearest points in the point cloud to the representative point (Tourapis ¶132-140, 144-149); and
constructing the plurality of three-dimensional patches based on the plurality of representative points and the nearest neighbouring points of the plurality of representative points (Tourapis ¶132-154 Segmentation Process; Wang FIG. 2, ¶28).
Consider claims 4 and 13, Tourapis, as modified by Wang, discloses the claimed invention wherein converting the extracted plurality of three-dimensional patches into the two-dimensional pictures comprises:
converting each extracted three-dimensional patch in the following way: taking the representative point in the three-dimensional patch as a start point, scanning on a two-dimensional plane according to a predetermined scan mode, and mapping other points in the three-dimensional patch to a scan path according to an increasing order of Euclidean distances to the representative point, to obtain one or more two-dimensional pictures, wherein a point in the three-dimensional patch nearer to the representative point is nearer to the representative point on the scan path, and attribute data of all points after mapping are unchanged (Tourapis FIGs. 12B, 13A-K, ¶197-207, 238, 271-285, 550-552; Wang ¶26, FIG. 2).
Consider claims 5 and 14, Tourapis, as modified by Wang, discloses the claimed invention wherein the predetermined scan mode comprises at least one of: square-spiral-shape scan, raster scan, or Z-shape scan (Tourapis FIGs. 12B, 13A-K, ¶550-552).
Consider claims 7 and 16, Tourapis, as modified by Wang, discloses the claimed invention wherein:
the method further comprises:
decoding the point cloud bitstream to output at least one quality enhancement parameter of the point cloud (Tourapis ¶370-382, 679-682; Wang FIG. 4A, ¶39, 43, 49-59);
performing quality enhancement on the attribute data of the converted two-dimensional pictures comprises:
performing quality enhancement on the attribute data of the converted two-dimensional pictures according to the at least one quality enhancement parameter output after decoding (Tourapis ¶370-382, 679-682; Wang FIG. 4A, ¶43, 49-59); and
[claim 16: determining a first quality enhancement parameter of the point cloud, and performing quality enhancement on the attribute data of the converted two-dimensional pictures comprises: performing quality enhancement on the attribute data of the converted two-dimensional pictures according to the determined first quality enhancement parameter; and the first quality enhancement parameter comprises at least one of (Tourapis ¶370-382, 679-682; Wang FIG. 4A, ¶43, 49-59):
the at least one quality enhancement parameter comprises at least one of:
the number of the three-dimensional patches extracted from the point cloud (Wang ¶43, 49-59);
the number of points in each two-dimensional picture (Wang ¶49-59);
arrangement of the points in each two-dimensional picture (Wang ¶40, 49-59);
at least one scan mode used when converting the plurality of three-dimensional patches into the two-dimensional pictures (Tourapis ¶550-552; Wang ¶49-59, FIG. 2);
a parameter of a quality enhancement network, wherein the quality enhancement network is used for performing quality enhancement on the attribute data of the two-dimensional pictures;
or a data feature parameter of the point cloud, wherein the data feature parameter is used for determining the quality enhancement network used in performing quality enhancement on the attribute data of the two-dimensional pictures, and the data feature parameter of the point cloud comprises at least one of: a type of the point cloud or a bit rate of an attribute bitstream of the point cloud.
Consider claim 17, Tourapis, as modified by Wang, discloses the claimed invention wherein at least one of the first quality enhancement parameters is obtained from a point cloud data source device of the point cloud (Tourapis FIG. 1, ¶102; Wang FIGs. 1A, 4A, ¶47).
Consider claims 10 and 19, Tourapis, as modified by Wang, discloses the claimed invention wherein determining the plurality of representative points in the point cloud comprises: selecting the plurality of representative points from the point cloud with a farthest point sampling algorithm (Wang ¶162).
Claims 6 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Tourapis, in view of Wang, as applied to claims 1-5, 7, 10-14, 16-17, and 19-20 above, and further in view of MPEG WG 7, hereinafter referred to as “MPEG,” (‘G-PCC codec description v12’).
Consider claims 6 and 15, Tourapis, as modified by Wang, discloses the claimed invention wherein updating the attribute data of the point cloud according to the attribute data of the two-dimensional pictures after quality enhancement comprises:
for each point in the point cloud, determining at least one corresponding point in the two-dimensional pictures after quality enhancement of the point (Tourapis ¶155-156, 176-178, 370-382, 679-682; Wang ¶51-59);
setting attribute data of the point in the point cloud to be equal to attribute data of the at least one corresponding point, when the number of the at least one corresponding point is 1 (Tourapis ¶155-158, 557, 679-682;);
setting the attribute data of the point in the point cloud to be equal to a weighted average value of the attribute data of the at least one corresponding point, when the number of the at least one corresponding point is greater than 1 (Tourapis ¶155-163, 491, 557, 679-682).
Tourapis, as modified by Wang, fails to specifically disclose:
skipping updating the attribute data of the point in the point cloud, when the number of the at least one corresponding point is 0.
In related art, MPEG discloses:
setting attribute data of the point in the point cloud to be equal to attribute data of the at least one corresponding point, when the number of the at least one corresponding point is 1 (MPEG 3.7 Attributes transfer (recoloring), Distance-weighted color transfer);
setting the attribute data of the point in the point cloud to be equal to a weighted average value of the attribute data of the at least one corresponding point, when the number of the at least one corresponding point is greater than 1 (MPEG 3.7 Attributes transfer (recoloring), Distance-weighted color transfer); and
skipping updating the attribute data of the point in the point cloud, when the number of the at least one corresponding point is 0 (MPEG 3.7 Attributes transfer (recoloring), Distance-weighted color transfer).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine the 0/1/>1 handling of MPEG into the decoding/encoding method of Tourapis, as modified by Wang, to predictably yield updating the attribute data based on a number of corresponding points after quality enhancement (Tourapis ¶155-163, 491, 557, MPEG 3.7).
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Tourapis, in view of Wang, as applied to claims 1-5, 7, 10-14, 16-17, and 19-20 above, and further in view of Budagavi (US 2019/0318509 A1).
Consider claim 18, Tourapis, as modified by Wang, fails to specifically disclose obtaining a second quality enhancement parameter; and encoding the second quality enhancement parameter and signalling the second quality enhancement parameter into the point cloud bitstream, wherein the second quality enhancement parameter is used when a decoding end performs quality enhancement on the point cloud output after decoding the point cloud bitstream.
In related art, Budagavi discloses obtaining a second quality enhancement parameter; and encoding the second quality enhancement parameter and signalling the second quality enhancement parameter into the point cloud bitstream, wherein the second quality enhancement parameter is used when a decoding end performs quality enhancement on the point cloud output after decoding the point cloud bitstream (Budagavi ¶79-80).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to incorporate the second quality enhancement parameter of Budagavi into the encoding/decoding method of Tourapis, as modified by Wang, to enable color smoothing enhancement at the decoder (Budagavi ¶79, Wang ¶59).
Allowable Subject Matter
Claims 8 and 9 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.
Relevant Prior Art
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 2021/0211703 A1 discloses geometry information signaling for occluded points in an
occupancy map video.
US 2020/0021856 A1 discloses systems for hierarchical point cloud compression.
Conclusion
THIS ACTION IS MADE FINAL. 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 ASHLEY HYTREK whose telephone number is (703)756-4562. The examiner can normally be reached M-F 9:00-5:00.
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/ASHLEY HYTREK/ Examiner, Art Unit 2665
/Stephen R Koziol/ Supervisory Patent Examiner, Art Unit 2665
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