DETAILED ACTION
This communication is being filed in response to the submission having a mailing date of 12/29/2025 in which a (3) month Shortened Statutory Period for Response has been set.
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 .
Acknowledgements
3. Upon new entry, claims (1 -20) remain pending for examination, of which (1, 10, 19) are the three parallel running independent claims on record. Claim 18 was amended.
Examiner thanks’ Applicant representative (Atty. Jeung Huh; Reg. No, 76,913) for the new list of amendments provided, for the detailed remarks and clarifications, and for the cooperation expediting the case.
Information Disclosure Statement
The Information Disclosure Statement (IDS) that was/were submitted on 12/29/2025 is in compliance with the provisions of 37 CFR 1.97. Accordantly, the IDS has been accepted and considered herein. See rejection section (6) for details.
Response to arguments
Applicant’s arguments have been carefully considered, but they’re not persuasive, for at least the following reasons:
The Examiner undersigned considers that the previously presented combined prior art (PA) on record, very well discloses the principles of the invention, and all the features as claimed associated with – a codec implementation of the same, employing “Feature coding for machines (FCM)” methodology, including the feature steps of refinement of restored feature tensors (FT), based on the single set of statistical parameters (i.e. encoded header syntax parameters (i.e. SEI/PPS/SPS, etc) obtained and processed via implemented NN; [Eimon];
… Ikonin similarly teaches a NN trained codec implementation of the same, for image reconstruction at (i.e. decoder 0286), by receiving encoded syntax of the multilayer bitstream, as shown in Fig. 9, wherein a layer being a feature tensor based on picture parameter/characteristics (Fig. 4), using NN trained functionality for regression; [Ikonin]
… which for the most part, was/were part of the common knowledge at the time of the invention.
5.2. Examiner considers that the no allowable subject matter has been yet identified in the claims. The claims language instead lists a set of well-known feature techniques, commonly used in codec Applications.
5.3. Applicant argues a failure to discloses the following topics:
5.3.1. The rejection fails to disclose: [determining a single set of statistical parameters associated with the original feature tensors" (page 6)]; the Examiner respectfully disagrees, because under the broadest reasonable interpretation doctrine, consistent with the instant specification and the common knowledge of one of ordinary skill in the art, both Eimon/Ikonin (combined and/or separately) disclose(s) the use of “encoded syntax element” as a single parameter (i.e. SEI/PPS/SPS, in NAL header syntax configs, defined and required by the codec standard); as detailed described in at least [Eimon; Ch. 6],
In this regard, it is also valid to point out, that the Instant Specifications (specs) defines “single set of statistical parameters” in at least [specs; 0004], as a SEI syntax generated by the encoder, transmitted to the decoder side, to be able to understand and process the incoming encoded data bitstream.
5.3.2. The rejection fails to disclose: […refining the set of restored feature tensors based on the single set of statistical parameters; page 6)]; Examiner also disagreed, because under the same BRI doctrine, at least Eimon discloses – (e.g. FT refinement, and layer update; [Eimon; Page 10]).
Regarding the rationale and motivation for the associated features/steps, and because no amendments presented in the filing, please refer to the recorded Rejection section (6).
Finally, the Office considers Applicant's arguments not persuasive, as applied rejection on record as a whole reads on the claimed construction, establishing the "Prima Facie" case of equivalent disclosures, on the basis of a person of ordinary skills in the art would have recognized the similar elements shown, or the same structural similarities shown, wherein such structure/methodology performs the same identical functions in substantially the same way, able to produce the same identical results.
_ See [MPEP – 2183]. Making a Prima Facie Case of Equivalence).
_ See In re Bond, 910 F.2d 831, 833, 15 USPQ2d 1566]; …when similar structure applies;
_ See Kemco Sales, Inc. vs. Control Papers., 208 F.3d 1352, 54 USPQ2d 1308] …when identical functionality is specified in the claim, in substantially the same way.
Claim rejection section
35 USC § 103
6. 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 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.
6.1. 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 non-obviousness.
6.2. Claim (1 -20) is/are rejected under 35 U.S.C. 103 as being unpatentable over the Eimon; et al. [“CE-2 - Reconstruction Refinement”] hereafter “Eimon”, in view of Ikonin; et al. [US 2023/0353764]; hereafter “Ikonin”).
Claim 1. (Original). Eimon discloses the principles of the invention substantially as claimed - A decoding device, comprising: a processor configured to: (e.g. a codec ecosystem of the same for image reconstruction, simulated under a similar Feature coding for machines (FCM) methodology, employing refinement of restored feature tensors based on the single set of statistical parameters, obtained from parameter points of an implemented NN, refined via a deviation curve of Figs. (2, 4); [pages 2 -3]).
Eimon specifically discloses - obtain, from a bitstream, multiple feature tensors associated with a picture, (e.g. see Fig. 1; [pages 2-3])
wherein the multiple feature tensors are compressed from respective original feature tensors associated with the picture; (e.g. see Figs. (3, 4); [pages 2-3])
determine a single set of statistical parameters associated with the original feature tensors; (e.g. see Figs. (3, 4); [pages 2-3])
restore the multiple feature tensors obtained from the bitstream to derive a set of restored feature tensors; (e.g. see Figs. (3, 4); [pages 2-3])
refine the set of restored feature tensors based on the single set of statistical parameters; (e.g. see Figs. (2, 4); [pages 2-3])
and perform an operation associated with the picture using the refined set of restored feature tensors; (e.g. see [pages 2-3]).
Given the teachings of Eimon as a whole, and under the obvious assumption and purpose of his papers, it is noted that some of the functional steps/components as listed (no encoder/decoder structural support disclosed), are missed or not fully described in the paper.
For the purpose of additional clarification and feature mapping, and in the same field of endeavor, Ikonin discloses a codec implementation (i.e. encoder/decoder) of the same, as shown in at least Figs. (7 A/B), in accordance with the codec formats [0003; 0194]; similarly employing NN convolutional techniques, as shown in Figs. 5-6.
Ikonin specifically teaches (e.g. a codec ecosystem of the same for image reconstruction at decoder side [0286], by receiving an encoded multilayer bitstream [0286], including a signaled syntax (i/e/ as shown in Fig. 9 [Ikonin; 0208]), being a layered feature tensor based on picture parameter/characteristics (i.e. Height & width, as shown in at least Fig. 4); also using deviation/probability functions for real value regression techniques; [0106].)
Therefore, it would have been obvious to one skilled in the art before the effective filing date of the claimed invention, to modify the methodology of Eimon’s paper with the codec architecture of Ikonin, in order to provide (e.g. codec quality improvement, data optimization, and efficient selection of information to be signaled from an encoder to a decoder; [Ikonin; 0090].)
Claim 2. (Original). Eimon/Ikonin discloses - The decoding device of claim 1, wherein the single set of statistical parameters is obtained from the bitstream; (e.g. bitstream syntax information allocated in the SEI; [Eimon; pages 9-10])
Claim 3. (Original). Eimon/Ikonin discloses - The decoding device of claim 1, wherein the single set of statistical parameters is determined based on previously obtained statistical parameters associated with another picture; (e.g. parameters obtained from the same or another picture, Fig. 4; [Ikonin; 0143]; the same motivation applies herein.)
Claim 4. (Original). Eimon/Ikonin discloses - The decoding device of claim 1, wherein the processor is further configured to receive an indication from the bitstream that indicates whether to obtain the single set of statistical parameters from the bitstream or based on statistical parameters associated with another picture; (e.g. see Table, for plurality of possible scenarios enabled; [Eimon; pages 9-10].)
Claim 5. (Original). Eimon/Ikonin discloses - The decoding device of claim 1, wherein the statistical parameters are associated with a normal distribution and comprise at least one of a mean value or a standard deviation value associated with the original feature tensors. (The same rationale and motivation apply herein, as given to Claim 1 above. In addition, see deviation/probability functions for real value regression techniques; [0106].)
Claim 6. (Original). Eimon/Ikonin discloses - The decoding device of claim 1, wherein the single set of statistical parameters is obtained from a supplemental enhancement information (SEI) message; (e.g. bitstream syntax information allocated in SEI; [Eimon; page 9].)
Claim 7. (Original). Eimon/Ikonin discloses - The decoding device of claim 6, wherein the single set of statistical parameters is obtained from the SEI message based on an indication in the SEI message that the single set of statistical parameters has been updated; (e.g. see C-code in the associated Table, where SEI updated using “IF” statement; [Eimon; pages 9-10]).
Claim 8. (Original). Eimon/Ikonin discloses -The decoding device of claim 1, wherein the bitstream further includes an indication of whether the single set of statistical parameters is derived based on the original feature tensors as a whole or as a sum of statistical parameters associated with each original feature tensor, (e.g. one element and or sum of elements may be used, Fig. 14; [Ikonin; 0205]); and wherein the processor is configured to refine the set of restored feature tensors based on the indication; (e.g. see [Eimon; pages 1-2].)
Claim 9. (Original). Eimon/Ikonin discloses - The decoding device of claim 1, wherein the processor is further configured to provide the refined set of restored feature tensors to a neural network that is split between the decoding device and an encoding device configured to generate the bitstream. (The same rationale and motivation apply as given to Claim 1 above.)
Claim 10. (Original). Eimon/Ikonin discloses - A decoding method, comprising: obtaining, from a bitstream, multiple feature tensors associated with a picture, wherein the multiple feature tensors are compressed from respective original feature tensors associated with the picture; determining a single set of statistical parameters associated with the original feature tensors; restoring the multiple feature tensors obtained from the bitstream to derive a set of restored feature tensors; refining the set of restored feature tensors based on the single set of statistical parameters; and performing an operation associated with the picture using the refined set of restored feature tensors. (Current lists all the same elements as recite in Claim 1 above, but in “Encoder method” form instead, and is/are therefore on the same premise. In addition, see similar generated deviation curve in Fig. 2, during data refinement, as detailed described in [Eimon; page 2]).
Claim 11. (Original). Eimon/Ikonin discloses - The decoding method of claim 10, wherein the single set of statistical parameters is obtained from the bitstream. (The same rationale and motivation apply as given to Claim 2 above.)
Claim 12. (Original). Eimon/Ikonin discloses - The decoding method of claim 10, wherein the single set of statistical parameters is determined based on previously obtained statistical parameters associated with another picture. (The same rationale and motivation apply as given to Claim 3 above.)
Claim 13. (Original). Eimon/Ikonin discloses - The decoding method of claim 10, further comprising receiving an indication from the bitstream that indicates whether to obtain the single set of statistical parameters from the bitstream or based on statistical parameters associated with another picture. (The same rationale and motivation apply as given to Claim 4 above.)
Claim 14. (Original). Eimon/Ikonin discloses - The decoding method of claim 10, wherein the statistical parameters are associated with a normal distribution and comprise at least one of a mean value or a standard deviation value associated with the original feature tensors. (The same rationale and motivation apply as given to Claim 5 above.)
Claim 15. (Original). Eimon/Ikonin discloses - The decoding method of claim 10, wherein the single set of statistical parameters is obtained from a supplemental enhancement information (SEI) message. (The same rationale and motivation apply as given to Claim 6 above.)
Claim 16. (Original). Eimon/Ikonin discloses - The decoding method of claim 15, wherein the single set of statistical parameters is obtained from the SEI message based on an indication in the SEI message that the single set of statistical parameters has been updated. (The same rationale and motivation apply as given to Claim 7 above.)
Claim 17. (Original). Eimon/Ikonin discloses - The decoding method of claim 10, wherein the bitstream further includes an indication of whether the single set of statistical parameters is derived based on the original feature tensors as a whole or as a sum of statistical parameters associated with each original feature tensor, and wherein the set of restored feature tensors is refined based on the indication. (The same rationale and motivation apply as given to Claim 8 above.)
Claim 18. (Amended). Eimon/Ikonin discloses - The decoding method of claim 10, further comprising providing the refined set of restored feature tensors to a neural network that is split between a decoding device and an encoding device configured to generate the bitstream. (The same rationale and motivation apply as given to Claim 9 above.)
Claim 19. (Original). Eimon/Ikonin discloses - An encoding device, comprising: a processor configured to: determine multiple feature tensors associated with a picture; determine a single set of statistical parameters associated with the multiple feature tensors; and encode the multiple feature tensors and the single set of statistical parameters into a bitstream. (Current lists all the same elements as recite in Claim 1 above, but in “Encoder form” instead, and is/are therefore on the same premise.)
Claim 20. (Original). Eimon/Ikonin discloses - The encoding device of claim 19, wherein the single set of statistical parameters includes at least one of a mean value or a standard deviation value associated with the multiple feature tensors. (Current lists all the same elements as recite in Claim 1 above, but in “Encoder device” form instead, and is/are therefore on the same premise. In addition, see similar generated deviation curve in Fig. 2, during data refinement, as detailed described in [Eimon; page 2]).
Prior Art Citations
7. The following List of prior art, made of record and not relied upon, is/are considered pertinent to applicant's disclosure:
7.1. Patent documentation
US 11,496,151 B1 Wang; Wei et al. G06N3/045; H03M7/3064;
US 12,101,107 B2 Wang; Wei et al. G06N3/045; H03M7/3064;
US 12,499,581 B2 Karabutov; et al. G06T9/00; H04N19/30; H04N19/172;
US 12,452,463 B2 Rosewarne; et al. H04N19/70; G06N3/0455; H04N19/46
US 12,556,703 B2 Rosewarne; et al. H04N19/124; G06N3/0464;
US 12,556,720 B2 Racape; et al. H04N19/186; H04N19/50; G06N3/045;
US 20230370622 A1 Racape; et al. H04N19/186; H04N19/50; G06N3/045;
US 20250324069 A1 Racape; et al. H04N19/176; H04N19/70;
US 20260006206 A1 Choi; et al. H04N19/136; H04N19/46;
US 20230353764 A1 Ikonin; Sergey et al. G06N3/0464; G06N3/0475;
7.2. Non-Patent Literature:
_ Related reconstruction refinement; April-2024; (AAPA).
_ Algorithm description of FCTM; April 2024; (AAPA).
_ Uses cases for video coding for machines; Tavakoli - 2019
_ Tensor decomposition learning for compression of multidimensional signals; Aidini - 2021
CONCLUSIONS
8. In view of the above Examiner’s considerations, THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.1 36(a). See also See MPEP 5 706.07(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 extension fee 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 date of this final action.
9. Any inquiry concerning this communication or earlier communications from the examiner should be directed to LUIS PEREZ-FUENTES (luis.perez-fuentes@uspto.gov) whose telephone number is (571) 270 -1168. The examiner can normally be reached on Monday-Friday 8am-5pm. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, WILLIAM VAUGHN can be reached on (571) 272-3922. The fax phone number for the organization where this application or proceeding is assigned is (571) 272 -3922. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated system, please call (800) 786 -9199 (USA OR CANADA) or (571) 272 -1000.
/LUIS PEREZ-FUENTES/
Primary Examiner, Art Unit 2481.
Prosecution Insights