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 filed 04 June 2026 have been fully considered but they are not persuasive.
Regarding claim 1, the Applicant contends nothing in Lee's paragraphs [0354]-[0367], and nothing about Lee's "predictive geometry information generator," suggests that Lee's vectors are used for attribute prediction, let alone for "determining ... attribute predictors for attributes of ... reconstructed points" whereby the claimed "attribute predictors" are determined "based on attributes of a reference point cloud and a motion vector field associated with the reconstructed points" as recited in independent claim 1. Lee's reference regions and their constituent voxels, derived through Lee's vectors, are used to generate predictive geometry information, not to project or predict attributes from a reference point cloud onto reconstructed points. The Office Action reliance on Lee's geometry inter-prediction vectors do not disclose or suggest using a motion vector field for attribute prediction and thus cannot be said to disclose or suggest the claimed step of "determining ... attribute predictors for attributes of ... reconstructed points" as recited in independent claim 1.
However, the Examiner respectfully disagrees. Lee discloses in paragraph [0391] that method of generating predicted geometry information described with reference to FIGS. 15 to 23 may also be applied to attribute information. That is, the attribute information intra-predictor 53011 and the attribute information inter-predictor 53012 may generate inter-predicted attribute information or intra-predicted attribute information by applying the aforementioned process of generating predictive geometry information (Lee: paragraph [0391]).
Regarding claim 1, the Applicant contends that Lee does not disclose or suggest that any reference point cloud or motion vector field is involved in its lifting transform process or that the "neighbor points" are points of a different point cloud (e.g., a reference point cloud). See, e.g., Lee at 11 [0192]-[0198] (explaining Lee's "lifting transform coding" process). Lee's techniques thus predict attributes based on spatial relationships among points within the same point cloud; they do not use attributes of a reference point cloud, nor do they employ a motion vector field associated with reconstructed points corresponding to locations in a reference point cloud for attribute prediction. Lee's cited disclosures, therefore, cannot be said to disclose or suggest "determining, based on attributes of a reference point cloud and a motion vector field associated with the reconstructed points, attribute predictors for attributes of the reconstructed points" as recited in independent claim 1.
However, the Examiner respectfully disagrees. The claim language neither precludes referencing points previously coded within the same frame, nor does the claim language distinguish that the reference point cloud is from another frame. The claim language may reasonably be interpreted as pertaining to any previously coded point as potential reference. Additionally, Lee discloses that point cloud coding may be performed in an intra mode or an inter mode, wherein intra coding references neighboring nodes in the same picture and inter coding references a previous frame (Lee: paragraph [0180]).
Claim Rejections - 35 USC § 102
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 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) 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Lee et al. (US 20230291895 A1).
Re claim 1, Lee discloses a method comprising:
determining, by a computing device and based on decoding points of a point cloud associated with content, reconstructed points of the point cloud (Lee: Fig. 11, Reconstruct geometry unit 11003; paragraph [0213]);
determining, based on attributes of a reference point cloud and a motion vector field associated with the reconstructed points (Lee: Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points; Fig. 11; paragraph [0218], output of Reconstruct geometry unit 11003 controls attribute decoding pipeline), attribute predictors for attributes of the reconstructed points (Lee: Fig. 11; paragraph [0218], output of Reconstruct geometry unit 11003 controls attribute decoding pipeline; Fig. 11, inverse lifting 11009; paragraph [0208]; paragraphs [0198]-[0199], attribute prediction); and
decoding, based on the determined attribute predictors, the attributes of the reconstructed points (Lee: Fig. 11; paragraphs [0205]-[0206], decoding).
Re claim 2, Lee discloses that the determining the attribute predictors comprises:
for each reconstructed point of the reconstructed points:
determining a point based on a motion vector, of the motion vector field, associated with the reconstructed point (Lee: Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points);
selecting, based on the point, one or more reference points from the reference point cloud (Lee: Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points); and
determining, based on attributes of the selected one or more reference points, an attribute predictor for an attribute of the reconstructed point (Lee: Fig. 11, inverse lifting 11009; paragraph [0208]; paragraphs [0198]-[0199], attribute prediction).
Re claim 3, Lee discloses that the determining the attribute predictors comprises:
for each reconstructed point of the reconstructed points:
determining a point based on a motion vector, of the motion vector field, associated with the reconstructed point (Lee: Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points);
selecting one or more reference points from the reference point cloud based on distances between the one or more reference points and the point (Lee: Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points); and
determining, based on attributes of the selected one or more reference points, an attribute predictor for an attribute of the reconstructed point (Lee: Fig. 11; paragraph [0218], output of Reconstruct geometry unit 11003 controls attribute decoding pipeline; Fig. 11, inverse lifting 11009; paragraph [0208]; paragraphs [0198]-[0199], attribute prediction).
Re claim 4, Lee discloses that the determining the attribute predictors comprises:
for a reconstructed point of the reconstructed points:
determining, based on translating the reconstructed point by a motion vector of the motion vector field, a point associated with the reconstructed point (Lee: Fig. 20).
Re claim 5, Lee discloses that the determining the attribute predictors comprises:
for all the reconstructed points:
determining, based on translating the reconstructed points by a same motion vector of the motion vector field, points associated with the reconstructed points (Lee: Fig. 20).
Re claim 6, Lee discloses that a motion vector of the motion vector field is associated with a plurality of cuboids spatially partitioning a volume containing a decoded geometry of the point cloud (Lee: Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points; Fig. 21).
Re claim 7, Lee discloses that the determining the attribute predictors comprises:
generating, based on a space partitioning tree corresponding to the reference point cloud, an attribute projection model (Lee: Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points; Fig. 21).
Re claim 8, Lee discloses that the decoding the attributes of the reconstructed points comprises:
decoding, from a bitstream, residual attributes indicating differences between the attributes of the reconstructed points and the attribute predictors (Lee: paragraphs [0191]-[0192], attribute prediction residual); and
determining, based on adding the attribute predictors and the decoded residual attributes, decoded attributes of the reconstructed points (Lee: paragraphs [0191]-[0192], attribute prediction residual).
Re claim 9, Lee discloses
determining, based on an already-coded reference point cloud, the reference point cloud, wherein the already-coded reference point cloud is used to decode a geometry of the point cloud (Lee: Fig. 11, Reconstruct geometry unit 11003; paragraph [0213]; Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points).
Re claim 10, Lee discloses that the reconstructed points are of a reconstructed geometry of the point cloud (Lee: Fig. 11, Reconstruct geometry unit 11003; paragraph [0213]).
Re claim 11, Lee discloses a method comprising:
determining, by a computing device and based on a reference point cloud and a first motion vector field, a decoded geometry, of a point cloud associated with content, comprising reconstructed points of the point cloud frame (Lee: Fig. 11, Reconstruct geometry unit 11003; paragraph [0213]; Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points); and
decoding, based on attributes of the reference point cloud and a second motion vector field, attributes of the reconstructed points (Lee: Fig. 11; paragraph [0218], output of Reconstruct geometry unit 11003 controls attribute decoding pipeline),
wherein the first motion vector field is associated with the reference point cloud, and the second motion vector field is associated with the reconstructed points (Lee: Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points).
Re claim 12, Lee discloses that the decoding the attributes of the reconstructed points comprises:
determining, based on attributes of the reference point cloud and the second motion vector field, attribute predictors for attributes of the reconstructed points (Lee: Fig. 11, inverse lifting 11009; paragraph [0208]; paragraphs [0198]-[0199], attribute prediction); and
decoding, based on the attribute predictors determined for the reconstructed points, the attributes of the reconstructed points (Lee: Fig. 11; paragraphs [0205]-[0206], decoding).
Re claim 13, Lee discloses that the decoding the attributes of the reconstructed points comprises using attribute predictors based on a quality of prediction of the attributes of the reconstructed points (Lee: [0196]-[0198], attribute prediction based on cumulative weighted process).
Re claim 14, Lee discloses that the decoding the attributes of the reconstructed points comprises:
for each reconstructed point of the reconstructed points:
determining a point based on a motion vector, of the second motion vector field, associated with the reconstructed point (Lee: Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points);
selecting one or more reference points from the reference point cloud, based on distances between the one or more reference points and the point (Lee: Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points);
determining, based on attributes of the selected one or more reference points, an attribute predictor for an attribute of the reconstructed point (Lee: Fig. 11; paragraph [0218], output of Reconstruct geometry unit 11003 controls attribute decoding pipeline; Fig. 11, inverse lifting 11009; paragraph [0208]; paragraphs [0198]-[0199], attribute prediction); and
decoding, based on the attribute predictor determined for the reconstructed point, an attribute of the reconstructed point (Lee: Fig. 11; paragraphs [0205]-[0206], decoding).
Re claim 15, Lee discloses that a motion vector of the second motion vector field is associated with a set of cuboids spatially partitioning a volume containing the decoded geometry of the point cloud (Lee: Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points; Fig. 21).
Re claim 16, Lee discloses a method comprising:
determining, by a computing device and based on attributes of points of a point cloud associated with content, attributes of reconstructed points of the point cloud (Lee: Fig. 4, Reconstruct geometry unit 40005; paragraph [0152]; Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points; Fig. 4, output of Reconstruct geometry unit 40005 controls attribute coding pipeline)
determining, based on attributes of a reference point cloud and a motion vector field associated with the reconstructed points, attribute predictors for the attributes of the reconstructed points (Lee: Fig. 4, output of Reconstruct geometry unit 40005 controls attribute coding pipeline; Fig. 11, inverse lifting 11009; paragraph [0208]; paragraphs [0198]-[0199], attribute prediction); and
encoding, based on the determined attribute predictors, the attributes of the reconstructed points (Lee: paragraphs [0140]-[0141], encoding).
Re claim 17, Lee discloses
wherein the reconstructed points are associated with a reconstructed geometry of the point cloud (Lee: paragraph [0152]),
wherein the determining the attributes of the reconstructed points comprises:
mapping attributes of a geometry of the point cloud to the reconstructed geometry (Lee: paragraph [0307], mapping between the geometry information and the attribute information may be performed), and
wherein the determining the attribute predictors is further based on the mapped attributes (Lee: paragraph [0306]).
Re claim 18, Lee discloses that the determining the attribute predictors comprises:
for each reconstructed point of the reconstructed points:
determining a point based on a motion vector, of the motion vector field, associated with the reconstructed point (Lee: Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points);
selecting one or more reference points from the reference point cloud, based on distances between the one or more reference points and the point (Lee: Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points); and
determining, based on attributes of the selected one or more reference points, an attribute predictor for an attribute of the reconstructed point (Lee: Fig. 4, output of Reconstruct geometry unit 40005 controls attribute decoding pipeline; Fig. 4, lifting 40010; paragraph [0143]; paragraphs [0198]-[0199], attribute prediction).
Re claim 19, Lee discloses
wherein the reconstructed points are associated with a reconstructed geometry of the point cloud (Lee: Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points), and
wherein the encoding the attributes comprises:
determining residual attributes based on differences between the attributes of the reconstructed geometry and the attribute predictors (Lee: paragraphs [0191]-[0192], attribute prediction residual); and
encoding, in a bitstream, the residual attributes (Lee: paragraphs [0191]-[0192], attribute prediction residual).
Re claim 20, Lee discloses
wherein the reconstructed points are associated with a reconstructed geometry of the point cloud (Lee: Fig. 20; paragraph [0367], points generated using motion vectors associated with reference points), and
wherein the attributes of the reconstructed geometry are encoded using the attribute predictors based on a quality of prediction of the attributes associated with the reconstructed geometry (Lee: [0196]-[0198], attribute prediction based on cumulative weighted process).
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.
Contact
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER G FINDLEY whose telephone number is (571)270-1199. The examiner can normally be reached Monday-Friday 9AM-5PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chris Kelley can be reached at (571)272-7331. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/CHRISTOPHER G FINDLEY/Primary Examiner, Art Unit 2482
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