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 Amendment and Argument
Applicant’s amendment and argument with respect to pending claims 1-3, 7 and 13-20 filed on 05/11/2026 have been fully considered but the argument has been rendered moot in view of a new ground(s) of rejection necessitated by the amendment of the claims.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-3 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
In claim 1 it is unclear as to what the claim refers by stating “a machine video application”, thereby renders the claim indefinite.
Dependent claims 2-3 are rejected based on their dependency from the rejected claim 1.
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 (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 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)(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) 1-3, 7 and 13-20 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Rosewarne et al. (US 20240205402 A1).
Regarding claim 1, Rosewarne teach the claim as follows:
A method for encoding features into a video frame, comprising:
processing a source video using a convolutional neural network to extract a sequence of feature maps (Figs. 1-9, ¶0069: The CNN backbone 114 receives the video frame data 113 and performs specific layers of an overall CNN, such as layers corresponding to the ‘backbone’ of the CNN. The backbone layers of the CNN may produce multiple tensors as output…Slicing the tensors 115 along the channel dimension results in extracting one feature map per channel, where the feature maps of a given tensor have a specific size that is determined from additional dimensions of the tensor); spatially arranging the sequence of feature maps in rectangular portions of the video frame (¶0161: FIG. 11 is a schematic block diagram showing a feature map packing arrangement 1100 in a two-dimensional array in the form of monochrome frame 1102. The feature maps of three layers, such as feature map 1110, feature map 1112, and feature map 1114, are arrangeable in the frame 1102); and encoding the video frame into a bitstream for a machine video application (¶0169: The frames 119 are input to the video encoder 120 … to produce the bitstream 121), the bitstream containing parameters for determining the location of each of the plurality of feature maps in the frame for restoring the sequence of feature maps by a decoder (¶0175: At the determine feature map placement step 1540 the packer module 522, under execution of the processor 205, determines the location at which each feature map will be placed in a frame…Feature maps belonging to a given group are sequentially packed and packed in the order in which the feature maps are listed in the respective group. ¶0179: At the encode metadata step 1580 the entropy encoder 638, under execution of the processor 205, encodes the feature map groupings 512 and quantisation ranges 516, i.e. the metadata 125 into the bitstream 121. The metadata 125 may be encoded using as the SEI message 1413. ¶0182: At the decode feature map groupings step 1610 the entropy decoder 720, under execution of the processor 205, decodes from the SEI message 1413 a structure indicating the assignment of each feature map of each layer to one or more groups of feature maps (i.e. the feature map groups 820)).
Regarding claim 2, Rosewarne teaches the method of claim 1, wherein the convolutional neural network comprises a plurality of processing layers and wherein the feature maps are extracted as an output of each layer (Figs. 1-9, ¶0069: The CNN backbone 114 receives the video frame data 113 and performs specific layers of an overall CNN, such as layers corresponding to the ‘backbone’ of the CNN. The backbone layers of the CNN may produce multiple tensors as output…Slicing the tensors 115 along the channel dimension results in extracting one feature map per channel, where the feature maps of a given tensor have a specific size that is determined from additional dimensions of the tensor…Feature maps of all layers are packed into planar video frames, such as packed feature map frames 117).
Regarding claim 3, Rosewarne teaches the method of claim 2, wherein the spatially arranging step includes arranging feature maps based on at least one of (1) features representing similar spatial characteristics, (2) features that represent similar object types,(3) features that are extracted using the same filters, (4) features from spatially neighboring regions; (5) features from the same layer of the CNN, and (6) features that relate to a specific task on the decoder side (¶0165: FIG. 12 is a schematic block diagram showing an alternative feature map packing arrangement 1200 in monochrome frame 1202. The feature map packing arrangement 1200 is suitable for feature map groupings where numerous groupings of four feature maps are present. The groupings of FIG. 12 may be based on spatial similarity between feature maps, resulting in groupings of similar feature maps).
Regarding claim 7, Rosewarne teach the claim as follows:
A method for decoding a video signal, the method comprising:
receiving an encoded bitstream having at least one frame partitioned with a plurality of rectangular regions having a plurality of feature maps arranged therein (¶0143: The bitstream 143 contains encoded syntax elements representing the captured frame data to be decoded. ¶0153: Decoded frames 147 are input to an unpacker module 810, where feature maps are extracted from each frame according to a packing format to produce unpacked feature maps 812. The unpacked feature maps 812 include sample values as present in the decoded frame 147. Packing formats are described further with reference to FIGS. 11-13), the bitstream containing parameters for determining the location of each of the plurality of feature maps in the frame for restoring an original sequence of the feature maps (¶0175: At the determine feature map placement step 1540 the packer module 522, under execution of the processor 205, determines the location at which each feature map will be placed in a frame…Feature maps belonging to a given group are sequentially packed and packed in the order in which the feature maps are listed in the respective group. ¶0179: At the encode metadata step 1580 the entropy encoder 638, under execution of the processor 205, encodes the feature map groupings 512 and quantisation ranges 516, i.e. the metadata 125 into the bitstream 121. The metadata 125 may be encoded using as the SEI message 1413. ¶0182: At the decode feature map groupings step 1610 the entropy decoder 720, under execution of the processor 205, decodes from the SEI message 1413 a structure indicating the assignment of each feature map of each layer to one or more groups of feature maps (i.e. the feature map groups 820));using the parameters, decoding the rectangular regions of the frame (¶0153, 0185: FIG. 8 is a schematic block diagram showing a feature map inverse quantiser and unpacker 148 as part of a distributed machine task system 100. Decoded frames 147 are input to an unpacker module 810, where feature maps are extracted from each frame according to a packing format to produce unpacked feature maps 812. The unpacked feature maps 812 include sample values as present in the decoded frame 147. Packing formats are described further with reference to FIGS. 11-13);
using the parameters, reconstructing the original sequence of feature maps from the spatially arranged feature maps in the frame (¶0153, 0185: FIG. 8 is a schematic block diagram showing a feature map inverse quantiser and unpacker 148 as part of a distributed machine task system 100. Decoded frames 147 are input to an unpacker module 810, where feature maps are extracted from each frame according to a packing format to produce unpacked feature maps 812. The unpacked feature maps 812 include sample values as present in the decoded frame 147. Packing formats are described further with reference to FIGS. 11-13).
Regarding claim 13, Rosewarne teaches the method of encoding of claim 1, wherein the feature maps are spatially arranged in the frame based on local similarities of the feature maps (¶0165: FIG. 12 is a schematic block diagram showing an alternative feature map packing arrangement 1200 in monochrome frame 1202. The feature map packing arrangement 1200 is suitable for feature map groupings where numerous groupings of four feature maps are present. The groupings of FIG. 12 may be based on spatial similarity between feature maps, resulting in groupings of similar feature maps).
Regarding claim 14, Rosewarne teaches the method of encoding of claim 1, wherein the feature maps are spatially arranged in the frame based on temporal similarities of the feature maps (¶0175: Groups of size two or three feature maps, with each feature map belonging to a different layer are packed collocated spatially but in different colour channels, as described with reference to FIG. 13).
Regarding claim 15, Rosewarne teaches the method of encoding of claim 1, wherein the encoder is one of an AVC, VVC, or HEVC compliant encoder (¶0065: VVC).
Regarding claim 16, Rosewarne teaches the method of encoding of claim 1, wherein the parameters include a width and a height of each feature map in the frame (¶0166: FIG. 13 is a schematic block diagram showing a feature map packing arrangement 1300 in a 4:2:0 chroma subsampled colour frame 1301... For two feature maps in adjacent layers, the larger feature map is placed in a luma plane 1302, such as feature map 1304. The smaller feature map of the two feature maps is placed in a chroma plane 1310, such as feature map 1314. Where a group includes three feature maps, the third feature map being smaller in size than the feature map placed in the chroma plane 1310…¶0006: height and width dimensions indicate the size of the feature maps at the particular stage of the CNN).
Regarding claim 17, Rosewarne teaches the method of decoding of claim 7, wherein the feature maps are spatially arranged in the frame based on local similarities of the feature maps (¶0165: FIG. 12 is a schematic block diagram showing an alternative feature map packing arrangement 1200 in monochrome frame 1202. The feature map packing arrangement 1200 is suitable for feature map groupings where numerous groupings of four feature maps are present. The groupings of FIG. 12 may be based on spatial similarity between feature maps, resulting in groupings of similar feature maps).
Regarding claim 18, Rosewarne teaches the method of decoding of claim 7, wherein the feature maps are spatially arranged in the frame based on temporal similarities of the feature maps (¶0175: Groups of size two or three feature maps, with each feature map belonging to a different layer are packed collocated spatially but in different colour channels, as described with reference to FIG. 13).
Regarding claim 19, Rosewarne teaches the method of decoding of claim 7, wherein the encoder is one of an AVC, VVC, or HEVC compliant encoder(¶0065: VVC).
Regarding claim 20, Rosewarne teaches the method of decoding of claim 1, wherein the parameters include a width and a height of each feature map in the frame (¶0166: FIG. 13 is a schematic block diagram showing a feature map packing arrangement 1300 in a 4:2:0 chroma subsampled colour frame 1301... For two feature maps in adjacent layers, the larger feature map is placed in a luma plane 1302, such as feature map 1304. The smaller feature map of the two feature maps is placed in a chroma plane 1310, such as feature map 1314. Where a group includes three feature maps, the third feature map being smaller in size than the feature map placed in the chroma plane 1310…¶0006: height and width dimensions indicate the size of the feature maps at the particular stage of the CNN).
The following is the prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Do et al. (US 20230070216 A1) describes a method, an apparatus, and a storage medium for compressing a feature map. Abstract.
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 NATHNAEL AYNALEM whose telephone number is (571)270-1482. The examiner can normally be reached M-F 9AM-5:30 PM ET.
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/NATHNAEL AYNALEM/Primary Examiner, Art Unit 2488
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