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 have been fully considered. Claim rejections under 112 second paragraph have been withdrawn. Claim interpretation under 112 (f) have been withdrawn.
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.
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.
Claims 1, 11, 14 is rejected under 35 U.S.C. 103 as being unpatentable over D11 and further in view of D2.2
With regard to claim 1, D1 teach at least one computer including a processor, a storage device connected to the processor, and an interface connected to the processor (see fig. 1, ¶ 30); a model configured to output inference data indicating importance of each region of multi-dimensional data (see ¶¶ 215-216: importance degree map); a compression level information generation unit configured to generate compression level information including a parameter for determining a data amount for each region of the multi-dimensional data based on the inference data (see ¶¶ 215-216: adaptive compression based on importance degree map, implicitly related to encoding parameters such as bit amount) ; and a compression processing to generate compressed data by lossy compression using the compression level information, wherein a data format of the compressed data has ensured compatibility with a transmission destination of the compressed data (see ¶¶ 215-216: generating compressed data based on importance degree, ¶ 57: lossy compression).
D1 does not explicitly that the encoded data is in a format that is compatible with a transmission destination, however it is implicit that the data format is compatible with a destination device, for example, so that the data can be later decoded and used. Alternatively, Examiner takes Official Notice to the fact that before the effective filing date of the claimed invention, it was extremely well known in the art to transmit encoded or compressed data to a transmission destination in a format that is compatible with the destination in order for the data to be useful at the target destination.
D1 teach wherein the multi-dimensional data is a moving image and wherein the compression level information generation unit generates the compression level information for generating the compressed data in which a data amount of an important region is large and a data amount of an unimportant region is small based on the inference data (see ¶¶ 215-216: bit amount allocated based on importance degree map, implicit that data amount is large for more important region and vice versa; see ¶¶ 219, 223: moving image).
D1 fails to explicitly teach further comprising: a preprocessing unit configured to execute a preprocess of processing the multi-dimensional data so as to reduce a calculation cost of the model, wherein the multi-dimensional data processed by the preprocessing unit is input to the model, wherein the preprocess is a process of reducing resolution of the multi-dimensional data, however D2 teach the missing features (see ¶¶ 23, 50: downscaling image to perform lookahead analysis - block level statistics using down sampled frames and generating quantization parameters using the statistics). One skilled in the art before the effective filing date would have found it obvious to incorporate known teachings of D2 in which quantization statistics are derived from down sampled images into the configuration of D1. In particular, it would have been obvious to generate statistics or in this case importance degree map based on down sampled image. The motivation would have been to reduce computational costs by down sampling the image prior to determining importance degree map.
With regard to claim 11, D1 teach wherein compression level information includes a parameter representing a compression degree for each compression unit of the compression processing (see ¶¶ 215-216: adaptive compression based on importance degree map, implicit that compression rate or parameter is changed based on the importance).
With regard to claim 14, D1 teach computer system according to claim 1, wherein the arithmetic device is at least one of a central processing unit (CPU), graphical processing unit (GPU), a field programmable gate array (FPGA), a hardware encoder/decoder, or an application specific integrated circuit (ASIC) (see ¶ 6: computer processor).
Claims 6, 12, 15-16 is rejected under 35 U.S.C. 103 as being unpatentable over D1 and further in view of D33 or in view of D4.4
With regard to claim 6, D1 teach at least one computer including a processor, a storage device connected to the processor, and an interface connected to the processor (see fig. 1, ¶ 30); a model configured to output inference data indicating importance of each region of multi-dimensional data (see ¶¶ 215-216: importance degree map); a compression level information generation unit configured to generate compression level information including a parameter for determining a data amount for each region of the multi-dimensional data based on the inference data (see ¶¶ 215-216: adaptive compression based on importance degree map, implicitly related to encoding parameters such as bit amount) ; and a compression processing to generate compressed data by lossy compression using the compression level information, wherein a data format of the compressed data has ensured compatibility with a transmission destination of the compressed data (see ¶¶ 215-216: generating compressed data based on importance degree, ¶ 57: lossy compression).
D1 does not explicitly that the encoded data is in a format that is compatible with a transmission destination, however it is implicit that the data format is compatible with a destination device, for example, so that the data can be later decoded and used. Alternatively, Examiner takes Official Notice to the fact that before the effective filing date of the claimed invention, it was extremely well known in the art to transmit encoded or compressed data to a transmission destination in a format that is compatible with the destination in order for the data to be useful at the target destination.
D1 teach wherein the multi-dimensional data is a moving image and wherein the compression level information generation unit generates the compression level information for generating the compressed data in which a data amount of an important region is large and a data amount of an unimportant region is small based on the inference data (see ¶¶ 215-216: bit amount allocated based on importance degree map, implicit that data amount is large for more important region and vice versa; see ¶¶ 219, 223: moving image).
D1 fails to explicitly teach importance degree of an area (see ¶¶ 215-216: importance degree map) and further teach object detection (see ¶ 224: object recognition), but fails to explicitly teach wherein, as an input for designating an important object to be detected, the model receives important object description information or information converted from the important object description information, and wherein the important object description information includes at least one of: a combination of an image and annotation data; and a natural language for designating the important object to be detected, and for each region of the multi-dimensional data, the model outputs a probability that the important object is included in the each region. However, D3 teach the missing features (see ¶¶ 46, 56, 67: object detection, bounding box of areas of interest which is read as annotation and probabilities associated with regions of interest, textual descriptions read as natural language description); See also D4 ¶¶ 18-19, 22: object detection probabilities along with bounding box which is read as annotation data of objects of importance.
One skilled in the art before the effective filing date would have found it obvious to combine the teachings to arrive at the claimed invention. In particular, it would have been obvious to incorporate known teachings of object detection with probabilities and annotation information as taught by D3 or D4 into the configuration of D1 yielding predictable and enhanced results. In particular, D1 is related to identifying regions of interest and generating importance of each region in order to use that information to compress the image. Separately, D3 and D4 teach identifying objects of importance and generating annotation information of the objects. It would have been obvious to incorporate information about object detection and annotation information as taught in D3 and D4 into D1 such that the compression algorithm in D1 can compress the image based on the type of objects and the annotation information.
With regard to claim 12, see discussion of claim 6.
With regard to claim 15, D1 teach computer system according to claim 6, wherein the arithmetic device is at least one of a central processing unit (CPU), graphical processing unit (GPU), a field programmable gate array (FPGA), a hardware encoder/decoder, or an application specific integrated circuit (ASIC) (see ¶ 6: computer processor).
With regard to claim 16, D1 teach computer system according to claim 12, wherein the arithmetic device is at least one of a central processing unit (CPU), graphical processing unit (GPU), a field programmable gate array (FPGA), a hardware encoder/decoder, or an application specific integrated circuit (ASIC) (see ¶ 6: computer processor).
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over D1 in view of D2 and further in view of D5.5
With regard to claim 4, D1 fails to explicitly teach wherein the computer system holds preprocess parameter management information for managing data in which an acquisition source from which the multi-dimensional data is acquired and a preprocess parameter for controlling the preprocess are associated with each other, and the preprocessing processing acquires the preprocess parameter by referring to the preprocess parameter management information based on the acquisition source of the multi- dimensional data, and executes the preprocess using the acquired preprocess parameter. However, D5 teach the missing features (see ¶¶ 24, 37, 50: compression parameters based on acquisition device; pre-processing using compression parameters based on acquisition device).
One skilled in the art before the effective filing date would have found it obvious to combine the teachings to arrive at the claimed invention. D1 and D5 both relate to compression of data. D1 teach compression based on importance map of the region in the image. Meanwhile, D5 teach adapting the compression based on acquisition source and in particular pre-processing based on acquisition source. It would have been obvious to incorporate known teachings of adapting the compression of data using information of the acquisition source as taught by D5 into the configuration of D1 yielding predictable and enhanced results. By taking into account the characteristics of the image acquisition device, better image compression targets can be achieved such as file size and quality (see D5 ¶ 2).
Claims 7-10, 13 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
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 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. 2020/0301595.
2 US Publication No. 2021/0306640.
3 US Publication No. 2021/0192727.
4 US Publication No. 2024/00547483
5 US Publication 2020/0320745.
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