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 with respect to claim(s) 1 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Claim(s) 1 - 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hannuksela et al (US 11,228,767, hereafter Hannuksela) in view of Joshi et al (US 2020/0186808, hereafter Joshi) in further view of Kang et al(US 11,589,065, hereafter Kang).
As per claim 1, Hannuksela discloses a method, comprising:
training a set of neural networks for intra prediction of a video block using pairs of partitioned portions of said video block and surrounding regions (column 29 lines 5 – 8); extracting further pairs of said video block and surrounding regions by iteratively using said set of neural networks as an additional intra coding mode for a codec (column 27 lines 60 – 65) wherein the training samples are encoded using the codec into which is implemented intra prediction using neural network using the initially trained network,; and
retraining said set of neural networks using said extracted further pairs to generate a set of neural networks for intra prediction (column 29 lines 8 – 15) wherein said set of neural networks are retrained on data coming from a coder comprising neural networks for intra prediction with fixed parameters (column 29 lines 54 – 56; For example, the initial parameters or weights for the neural net may be defined in a video/image coding standard.); and
encoding a video block using intra prediction with said retrained set of neural networks.
However, Hannuksela does not teach wherein the parameters of each neural network of the set of neural network are initialized with the neural network parameters obtained at the endo of the iteration of a previous neural network of the set of neural networks;
wherein said training a set of neural networks for intra prediction comprises: for fully connected neural networks, flattening a context surrounding the current block into a vector, feeding said flattened vector into said neural network, and reshaping said flattened vector to a shape of the video block or for a convolutional neural network, splitting a context surrounding the current block into two portions, feeding said two portions into a stack of convolutional layers, merging said convolutional layer output and inserting said result into a stack of transpose convolutional layers.
In the same field of endeavor, Joshi teaches wherein the parameters of each neural network of the set of neural network are initialized with the neural network parameters obtained at the endo of the iteration of a previous neural network of the set of neural networks (¶ 52; In a CNN, the classification (e.g., regression) portion can be a set of fully connected layers. The fully connected layers can be thought of as looking at all the input features in order to generate a high-level classifier. Several stages (e.g., a series) of high-level classifiers eventually generate the desired classification (e.g., regression) output.; Applicant’s parameters appear to be inputs which when applied to neural networks are output at each layer and may be used as input to the next neural network layer until the final layer is reached based on the design);
wherein said training a set of neural networks for intra prediction comprises: for fully connected neural networks, flattening a context surrounding the current block into a vector, feeding said flattened vector into said neural network, and reshaping said flattened vector to a shape of the video block, for non-split blocks, only blocks where a prediction cost of a neural network mode is less than or equal to a threshold multiple of a lowest prediction cost among other intra prediction modes, or for split blocks, blocks where a neural network mode was selected, or for a convolutional neural network, splitting a context surrounding the current block into two portions, feeding said two portions into a sack of convolutional layers, merging said convolutional layer output and inserting said result into a stack of transpose convolutional layers (¶ 53 56, 144,and 166).
However, Hannuksela or Joshi does not explicitly teach and wherein a luminance block is extracted from a luminance channel of an image containing the video block, whereas the luminance context X is extracted from a luminance channel of its reconstructed image.
In the same field of endeavor, Kang teaches teach and wherein a luminance block is extracted from a luminance channel of an image containing the video block, whereas the luminance context X is extracted from a luminance channel of its reconstructed image (Figure 5; column 13 lines 29 – 37 and see claim 1).
Therefore, it would have been obvious for one of ordinary skill in the art at the time the invention was effectively filed to modify the invention of Hannuksela in view of Joshi in further view of Kang. The advantage is an improved intra prediction process.
Regarding claim 2, arguments analogous to those presented for clam 1 are applicable for claim 2.
Regarding claim 3, arguments analogous to those presented for clam 1 are applicable for claim 3.
Regarding claim 4, arguments analogous to those presented for clam 1 are applicable for claim 4.
As per claim 5, Hannuksela discloses the method of claim 2, further configured to: encode a video block using intra prediction with said retrained set of neural networks (column 29 lines 8 – 15).
As per claim 6, Hannuksela discloses the method of Claim 2, further configured to: decode a video block using intra prediction with said retrained set of neural networks (column 29 lines 8 – 15).
As per claim 7, Hannuksela discloses the method of claim 1 , wherein the partitioned portions are rectangular (column 11 lines 61 – 63).
As per claim 8, Hannuksela discloses the method of claim 1 , wherein block height is added to characteristics of said video block (column 11 lines 61 – 63).
As per claim 9, Hannuksela discloses the method of claim 1 , wherein characteristics are used to extract a block from its reconstruction (column 11 lines 61 – 63).
As per claim 10, Hannuksela discloses the method of claim 9 wherein a set B of characteristics of blocks results from said partitioning (column 11 lines 61 – 63).
As per claim 11, Hannuksela discloses the method of claim 1 , wherein a number of pairs of partitioned portions extracted is limited (column 11 lines 61 – 63).
Regarding claim 12, arguments analogous to those presented for clam 1 are applicable for claim 12.
Further claim 12, Hannuksela discloses at least one of (i) an antenna configured to receive a signal, the signal including the video block, (ii) a band limiter configured to limit the received signal to a band of frequencies that includes the video block, and (iii) a display configured to display an output representative of a video block (column 4 lines 19 – 28 and column 5 lines 1 – 10).
Regarding claim 13, arguments analogous to those presented for clam 1 are applicable for claim 13.
Regarding claim 14, arguments analogous to those presented for clam 1 are applicable for claim 14.
Regarding claim 15, arguments analogous to those presented for clam 2 are applicable for claim 15.
Regarding claim 16, arguments analogous to those presented for clam 7 are applicable for claim 16.
Regarding claim 17, arguments analogous to those presented for clam 8 are applicable for claim 17.
Regarding claim 18, arguments analogous to those presented for clam 9 are applicable for claim 18.
Regarding claim 19, arguments analogous to those presented for clam 10 are applicable for claim 19.
Regarding claim 20, arguments analogous to those presented for clam 11 are applicable for claim 20.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHIKAODILI E ANYIKIRE whose telephone number is (571)270-1445. The examiner can normally be reached 8 am - 4:30 pm.
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, David Czekaj can be reached on 571-272-7327. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/CHIKAODILI E ANYIKIRE/Primary Examiner, Art Unit 2487