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 .
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 13 January 2025 and 5 February 2025 are being considered by the examiner.
Claim Interpretation
Claims 11-15 recite “computer program product…comprises one or more computer readable storage mediums” where paragraph [0033] of the specification specifically states “A computer-readable storage medium, as used herein, is not to be construed as being transitory signals per se.” The claims are thus interpreted to exclude signals and are therefore claiming statutory subject matter.
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.
Claims 1-4, 6-14 and 16-19 are rejected under 35 U.S.C. 103 as being unpatentable over Rai et al. (US 2022/0180101) in view of Roy Chowdhury et al. (US 2020/0082540).
Regarding claim 1, Rai et al. disclose a computer-implemented method of predicting one or more motions of a video, said method comprising:
(a) generating a plurality of temporal views of the video, wherein the temporal views of the video comprise a plurality of different video clips with varying motion characteristics (Figure 3, steps 332-334 and paragraphs [0036]-[0037], the video sequence is partitioned, i.e. a plurality of temporal views are generated. Paragraphs [0044]-[0045] explain the different types of motions that can occur in the video, such as object manipulations, general body movement, playing musical instruments, etc.);
(b) varying spatial characteristics of the plurality of the video clips (Figure 3, 336-338, paragraph [0038]: latent representations, and paragraph [0039]: context representation, and different spatial locations.); and
(c) feeding the video clips, and the different spatial fields, into an algorithm, wherein the algorithm matches varying views of the video clips across spatial and temporal dimensions in latent space to predict the one or motions of the video (Figure 3, 340 and paragraphs [0040]-[0042], predicting blocks, and paragraphs [0044]-[0046] explains body movement, etc., thus the prediction includes one or more motions of the video.).
Rai et al. disclose of different spatial locations in paragraph [0039], however, fails to explicitly teach wherein the varying comprises generating local spatial fields and global spatial fields of the video clips.
Roy Chowdhury et al. disclose of video comprising local spatial fields and global spatial fields (Paragraphs [0004] and [0009].).
Hence the prior art includes each element claimed although not necessarily in a single prior art reference, with the only difference between the claimed invention and the prior art being the lack of the actual combination of the elements in a single prior art reference. In combination Rai et al. performs the same function as it does separately of generating different spatial field of the video clips, and Roy Chowdhury et al. performs the same function as it does separately of local spatial fields and global spatial fields.
Therefore, one of ordinary skill in the art before the effective filing date of the claimed invention could have combined the elements as claimed by known methods, and that in combination, each element merely performed the same function as it does separately. The results of the combination would have been predictable and resulted in generating local spatial fields and global spatial fields of the video clips.
Therefore, the claimed subject matter would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention.
Regarding claim 2, Rai et al. and Roy Chowdhury et al. disclose the method of claim 1, further comprising a step of generating an output of the one or more predicted motions of the video (Rai et al.: Figure 3, 340 and paragraphs [0040]-[0042], predicted blocks are generated and output.).
Regarding claim 3, Rai et al. and Roy Chowdhury et al. disclose the method of claim 1, wherein the temporal views of the video comprise a collection of video clips sampled at a certain video frame rate (Rai et al.: Paragraph [0068]: 30 fps.).
Regarding claim 4, Rai et al. and Roy Chowdhury et al. disclose the method of claim 1, wherein the algorithm comprises a loss of function algorithm (Rai et al.: Figure 4, 432 and the last sentence of paragraph [0047].).
Regarding claim 6, Rai et al. and Roy Chowdhury et al. disclose the method of claim 1, wherein the prediction occurs in a self-supervised manner (Rai et al.: Paragraphs [0001] and [0026].).
Regarding claim 7, Rai et al. and Roy Chowdhury et al. disclose the method of claim 1, wherein the prediction occurs without the use of ground-truth bounding boxes (Both Rai et al. and Roy Chowdhury et al. fail to teach of using ground-truth bounding boxes, and thus the prediction in Rai et al. occurs without the use of ground-truth bounding boxes as claimed.).
Regarding claim 8, Rai et al. and Roy Chowdhury et al. disclose the method of claim 1, wherein the prediction occurs without the use of labeled data sets (Rai et al.: Paragraph [0030]: “instead of labels” and thus the prediction occurs without the use of labeled data sets.).
Regarding claim 9, Rai et al. and Roy Chowdhury et al. disclose the method of claim 1, wherein the prediction occurs without the use of object detectors (Both Rai et al. and Roy Chowdhury et al. fail to teach of object detectors, and thus the prediction in Rai et al. occurs without the use of object detectors.).
Regarding claim 10, Rai et al. and Roy Chowdhury et al. disclose the method of claim 1, wherein the method is utilized for group activity recognition (GAR), video analysis, video monitoring, interpretation of social settings, training, sport-related training, or combinations thereof (Rai et al.: Paragraphs [0043]-[0045]: the method is used for video analysis.).
Regarding claim 11, this claim is rejected under the same rationale as claim 1, and furthermore Rai et al. also disclose a computer program product that comprises one or more computer readable storage mediums having program code embodied therewith (Figure 9).
Regarding claim 12, this claim is rejected under the same rationale as claim 2.
Regarding claim 13, Rai et al. and Roy Chowdhury et al. disclose the computer program product of claim 11, wherein the computer program product further comprises the algorithm (Rai et al.: Figures 4 and 9.).
Regarding claim 14, this claim is rejected under the same rationale as claim 4.
Regarding claim 16, this claim is rejected under the same rationale as claim 1, and furthermore Rai et al. also disclose a system (Figure 9), comprising: a memory for storing a computer program for predicting one or more motions of a video (Figure 9, 908); and a processor connected to said memory (Figure 9, 904).
Regarding claim 17, this claim is rejected under the same rationale as claim 2.
Regarding claim 18, this claim is rejected under the same rationale as claim 13.
Regarding claim 19, this claim is rejected under the same rationale as claim 4.
Claims 5, 15 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Rai et al. (US 2022/0180101) in view of Roy Chowdhury et al. (US 2020/0082540) and further in view of Makrinich et al. (US 2021/0313052).
Regarding claim 5, Rai et al. and Roy Chowdhury et al. disclose the method of claim 1.
Rai et al. and Roy Chowdhury et al. fail to teach wherein the algorithm comprises an artificial neural network.
Makrinich et al. disclose wherein an algorithm comprises an artificial neural network (Paragraph [0056].).
Therefore, it would have been obvious to “one of ordinary skill” in the art before the effective filing date of the claimed invention to use the teachings of Makrinich et al. to make the algorithm taught by the combination of Rai et al. and Roy Chowdhury et al. an artificial neural network. The motivation to combine would have been in order to make use of the known advantages of an artificial neural network, such as non-linear modeling and handling of incomplete data, thus improving the prediction.
Regarding claim 15, this claim is rejected under the same rationale as claim 5.
Regarding claim 20, this claim is rejected under the same rationale as claim 5.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Curcio et al. (US 2014/0161354) disclose a method and apparatus for semantic extraction and video remix creation.
Zhang et al. (US 2024/0169726) disclose computer vision-based surgical workflow recognition system using natural language processing techniques.
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/STEPHEN G SHERMAN/Primary Examiner, Art Unit 2621
10 September 2026
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