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 .
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 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.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-5, 9-12, 14, 19-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by D1.1
With regard to claim 1, D1 teach obtaining geometry information and attribute information of points in a point cloud (see ¶ 537: geometry and attribute information); determining prediction values of the attribute information of the points in the point cloud according to the geometry information of the points in the point cloud (see ¶¶ 540, 548: prediction value of attribute information; prediction value calculated using reference node, which is determined based on the geometry information); determining residual values of the attribute information of the points in the point cloud according to the prediction values of the attribute information of the points in the point cloud (see ¶ 590: residual value); and processing the residual values of the attribute information of the points in the point cloud with a first encoding process, lossless encoding being performed on a residual value of attribute information of at least one point in the point cloud in the first encoding process (see ¶¶ 590-592: encoding of residual values; ¶ 651: lossless encoding).
With regard to claim 2, D1 teach wherein the at least one point comprises N points and N is an integer multiple of 2, or the at least one point comprises N points and each two neighboring points in the N points have an equal interval (see fig. 1: point cloud with N points multiple of 2).
With regard to claim 3, D1 teach wherein performing lossless encoding on the residual value of the attribute information of the at least one point in the point cloud comprises: performing, according to a preset interval, lossless encoding on residual values of attribute information of points spaced at preset intervals in the point cloud (see ¶¶ 590-592, 651: lossless encoding of residual values).
With regard to claim 4, D1 teach further comprising: performing level of detail (LOD) partition on the point cloud according to the geometry information of the points in the point cloud to obtain a plurality of detail representation layers of the point cloud, wherein each detail representation layer comprises one or more points (see ¶¶ 521, 532: level of detail layers; see also ¶ 609); and wherein performing lossless encoding on the residual value of the attribute information of the at least one point in the point cloud comprises: performing lossless encoding on a residual value of attribute information of at least one point in at least one detail representation layer in the plurality of detail representation layers (see ¶¶ 590-592, 651: lossless encoding of residual values).
With regard to claim 5, D1 teach method of claim 4, wherein performing lossless encoding on the residual value of the attribute information of the at least one point in the at least one detail representation layer in the plurality of detail representation layers comprises: obtaining, from the plurality of detail representation layers, at least one first type of detail representation layer in which a total number of points is less than or equal to a first preset value and at least one second type of detail representation layer in which a total number of points is greater than the first preset value (see ¶¶ 521, 532: level of detail layers comprising plurality of layers with plurality of points, implicitly consist of points that are less than some number or greater than some number); performing lossless encoding on residual values of attribute information of all points in the first type of detail representation layer; and performing lossless encoding on a residual value of attribute information of at least one point in the second type of detail representation layer (see ¶¶ 590-592, 651: lossless encoding of residual values). The level of detail layers typically involve varying number of points depending on the level of detail to be preserved.
With regard to claim 9, D1 teach wherein performing lossless encoding on the residual value of the attribute information of the at least one point in the point cloud comprises: skipping the at least one point for which lossless encoding is performed on the residual value of the attribute information, in the process of quantizing the residual values of the attribute information of the points in the point cloud; setting a quantization step size of the at least one point for which lossless encoding is performed on the residual value of the attribute information to be 1; or setting a quantization parameter (QP) of the at least one point for which lossless encoding is performed on the residual value of the attribute information to be a target value, wherein the target value is a QP value corresponding to a quantization step size of 1 (see ¶¶ 424, 443, 526: quantization parameter maybe selected or changed; ¶¶ 590-592, 651: lossless encoding implicit that the quantization parameter is set to or approaches 1). Note that the quantization parameter is recognized to be a result effective variable that can be optimized through routine experimentation.
With regard to claim 10, see discussion of claim 1, which describes the encoding process. The steps of the decoding process are simply the inverse of encoding process as described in the discussion of claim 1. See also for example figs. 49, 55, ¶¶ 528-556: decoding steps.
With regard to claim 11, D1 teach method of claim 10, wherein decoding the bitstream of the point cloud to obtain the residual values of the attribute information of the points in the point cloud comprises: decoding the bitstream of the point cloud to obtain first information, wherein the first information is indicative of a point of which a residual value of attribute information is determined to be subject to lossless encoding (see ¶ 972: lossless enable flag); decoding the bitstream of the point cloud to obtain residual information of attribute information of a point to-be-decoded in the point cloud and determining whether the residual information of the attribute information of the point to- be-decoded in the point cloud is determined to be subject to lossless encoding according to the first information (see ¶¶ 610, 614, 616, 972: decoding residual information); determining the residual information of the attribute information of the point to-be- decoded as a residual value of the attribute information of the point to-be-decoded based on a determination that the residual information of the attribute information of the point to-be- decoded is determined to be subject to lossless encoding (see ¶¶ 610, 614, 616, 972: decoding residual information, ¶ 972: using lossless flag); and determining residual information of the attribute information of the point to-be-decoded after inverse quantization as the residual value of the attribute information of the point to-be- decoded based on a determination that the residual information of the attribute information of the point to-be-decoded is determined to be subject to lossy encoding (see ¶¶ 610, 614, 616: inverse quantization of residual values).
With regard to claim 12, D1 teach the first information comprises N, and N is a total number of points in the point cloud of which residual values of attribute information have been subject to lossless encoding; N is an integer multiple of 2; or each two neighboring points in N points have an equal interval (see fig. 1: N number of points in the point cloud and is a multiple of 2).
With regard to claim 14, D1 teach method of claim 11, further comprising: performing level of detail (LOD) partition on the point cloud according to the geometry information of the points in the point cloud to obtain a plurality of detail representation layers of the point cloud, wherein each detail representation layer comprises one or more points (see ¶¶ 521, 532, 574, 609: level of detail layers).
With regard to claim 19, see discussion of claim 10.
With regard to claim 20, see discussion of claim 11.
Claims 6-8, 13, 15-18 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.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AVINASH YENTRAPATI whose telephone number is (571)270-7982. The examiner can normally be reached on 8AM-5PM.
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/AVINASH YENTRAPATI/Primary Examiner, Art Unit 2672
1 US Publication No. 2022/0028120.
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