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 filed 19 May 2026 have been fully considered but they are not persuasive.
Regarding the arguments on page 8-11, it is stated that “CN113099161 fails to teach or fairly suggest "whether to synthesize the current frame and each subsequent current frame of a video sequence by a generative neural network without entropy coding”.
However, the examiner disagrees and asserts that the CN reference teaches the determining step (i.e. neural network used to encode the motion information of the region of interest (ROI). Entropy coding is used for lossless compression and the neural network based coding can be used for coding which does not require lossless coding) [abs; step 2]. Further, the CN references teaches: fusing each reconstructed frame according to the time axis to obtain the reconstructed conference video [step 5; page 6 of PDF provided].
Therefore, the rejection, as set forth in the previous office action, stands.
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.
Claim(s) 1,8,9, and 16 is/are rejected under 35 U.S.C. 102(a)(1)(2) as being anticipated by CN113099161.
Regarding claim 1, CN meets the claim limitations, as follows:
A method comprising:
computing, by one or more processors of a computing system, a relative difference metric describing differences in features between a current frame and a reference frame (i.e. key point displacement coding information would be a difference metric between the current frame and reconstructed frame) [abs]; and
determining, by the one or more processors, based on the relative difference metric, whether to synthesize the current frame and each subsequent current frame of a video sequence by a generative neural network without entropy coding (i.e. neural network used to encode the motion information of the region of interest (ROI). Entropy coding is used for lossless compression and the neural network based coding can be used for coding which does not require lossless coding. These steps are performed for each frame and fused to form a reconstructed video) [abs; step 2,5].
Claim 8 is rejected using similar rationale as claim 1. This is the decoder of claim 1. Decoders perform the inverse operation as the encoder.
Claim 9 is rejected using similar rationale as claim 1.
Claim 16 is rejected using similar rationale as claim 8.
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 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.
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.
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 of this title, 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 set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied 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.
Claim(s) 2, 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over CN in view of Zhang US 20220385907.
Regarding claim 2, CN do/does not explicitly disclose(s) the following claim limitations:
wherein computing the relative difference metric further comprises: inputting, by the one or more processors, the current frame and the reference frame into a learning model; and outputting, by the one or more processors, current keypoints of the current frame and reference keypoints of the reference frame.
However, in the same field of endeavor Zhang discloses the deficient claim limitations, as follows:
wherein computing the relative difference metric further comprises: inputting, by the one or more processors, the current frame and the reference frame into a learning model (i.e. input frames into NN (learning model)) [5,44,96]; and outputting, by the one or more processors, current keypoints of the current frame and reference keypoints of the reference frame (i.e. encoded in terms of key frames) [96].
It would have been obvious to one with ordinary skill in the art at the time of filing to modify the teachings of CN with Zhang to compute the relative difference metric further comprises: inputting, by the one or more processors, the current frame and the reference frame into a learning model; and outputting, by the one or more processors, current keypoints of the current frame and reference keypoints of the reference frame.
It would be advantageous because "“the machine learning system can increase the compression and/or decompression performance, bitrate, quality, and/or efficiency for a particular set of data.” [45].
Therefore, it would have been obvious to one with ordinary skill, in the art at the time of filing, to modify the teachings of CN with Zhang to obtain the invention as specified in claim 2.
Claim 10 is rejected using similar rationale as claim 2.
Claim(s) 3 and 11 is/are rejected under 35 U.S.C. 103 as being unpatentable over CN and Zhang in view of Valin US 20140286399.
Regarding claim 3, CN and Zhang do/does not explicitly disclose(s) the following claim limitations:
wherein computing the relative difference metric further comprises: calculating, by the one or more processors, an absolute difference of the current keypoints and the reference keypoints
However, in the same field of endeavor Valin discloses the deficient claim limitations, as follows:
wherein computing the relative difference metric further comprises: calculating, by the one or more processors, an absolute difference of the current keypoints and the reference keypoints [63].
It would have been obvious to one with ordinary skill in the art at the time of filing to modify the teachings of CN and Zhang with Valin to have wherein computing the relative difference metric further comprises: calculating, by the one or more processors, an absolute difference of the current keypoints and the reference keypoints.
It would be advantageous because “Unfortunately, such systems and methods have drawbacks such as blurriness due to loss of energy detail, activity masking overhead, and inefficient representation of coefficients. Embodiments of the present disclosure address these and other issues.” [2-3].
Therefore, it would have been obvious to one with ordinary skill, in the art at the time of filing, to modify the teachings of CN and Zhang with Valin to obtain the invention as specified in claim 3.
Claim 11 is rejected using similar rationale as claim 3.
Claim(s) 17 is/are rejected under 35 U.S.C. 103 as being unpatentable over CN and in view of Ozcan US 20220012850.
Claim 17 is rejected using similar rationale as claim 1 and further below.
Ozcan meets the claim limitations, as follows:
A method comprising: training, by one or more processors of a computing system, a generative neural network without a discriminator; and jointly with a discriminator (i.e. FIG. 6 illustrates the results of two different trained deep neural networks 36 including the GAN network 36 disclosed above and a convolution neural network (CNN) 36. The CNN is the same as the generator network trained without using the discriminator and the adversarial loss terms. The two networks 36 were trained on the same dataset for similar number of iterations (˜40 epochs).) [43-46].
Allowable Subject Matter
Claims 4-7 and 12-15 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.
Regarding claim 4, Zhang meets the claim limitations, as follows:
The method of claim 3, wherein computing the relative difference metric further comprises: dividing, by the one or more processors, (i.e. frames divided in groups of N frames for video processing) [181].
The prior arts do not disclose:
the absolute difference by a mean of a moving window, wherein the moving window comprises a previous absolute difference
Regarding claim 7, the prior arts do not disclose:
comparing, by the one or more processors, the relative difference metric to a relative difference threshold.
Conclusion
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.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JARED T WALKER whose telephone number is (571)272-1839. The examiner can normally be reached M-F: 7:00 - 3:00 Mountain.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Nasser Goodarzi can be reached on 571-272-4195. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Jared Walker/Primary Examiner, Art Unit 2426
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