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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 03/28/2025 has been considered by the examiner.
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 pre-AIA 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 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.
Claims 1, 2, 4, 7, 8, 10, 12, and 13 are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by WANG et al. (US 20190020880 A1), hereinafter referenced as WANG.
Regarding claim 1, WANG teaches one or more processors (Fig. 1, Paragraph [0103] - WANG discloses video encoder 28, video decoder 48, audio encoder 26, audio decoder 46, encapsulation unit 30, retrieval unit 52, and decapsulation unit 50 each may be implemented as any of a variety of suitable processing circuitry, as applicable, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic circuitry, software, hardware, firmware or any combinations thereof. See also Paragraph [0257].) comprising:
one or more circuits (Fig. 1, Paragraph [0103] - WANG discloses video encoder 28, video decoder 48, audio encoder 26, audio decoder 46, encapsulation unit 30, retrieval unit 52, and decapsulation unit 50 each may be implemented as any of a variety of suitable processing circuitry, as applicable, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic circuitry, software, hardware, firmware or any combinations thereof. See also Paragraph [0257].) to:
extract a plurality of regions (Fig. 1, Paragraph [0082] - WANG discloses two or more packed regions of video data may overlap, as indicated by region-wise packing information. Content preparation device 20 may generate a region-wise packing box (RWPB) that defines positions and sizes of the various packed regions, which may thus indicate an overlap between two or more packed regions.)
from an image to be encoded using an image encoding process (Fig. 1, Paragraph [0082] - WANG discloses content preparation device 20 may obtain spherical video data using video source 24, e.g., by capturing and/or generating (e.g., rendering) the spherical video data. The spherical video data may also be referred to as projected video data. Content preparation device 20 may form packed video data from the projected video data (or spherical video data) for ease of encoding, processing, and transport.);
generate a plurality of encoded regions by encoding each of the plurality of regions using the image encoding process (Fig. 1, Paragraph [0246] - WANG discloses content preparation device 20 may then provide the first packed region to video encoder 28, to cause video encoder 28 to encode the first packed region (206). Paragraph [0247] - WANG further discloses content preparation device 20 provides the non-overlapping portion of the second packed region to video encoder 28, to cause video encoder 28 to encode the second packed region, excluding the overlap with the first packed region.);
and generate a media package (Fig. 1, Paragraph [0081] - WANG discloses video encoder 28 produces a stream of encoded video data. An elementary stream is a single, digitally coded (possibly compressed) component of a representation. For example, the coded video or audio part of the representation can be an elementary stream. An elementary stream may be converted into a packetized elementary stream (PES) before being encapsulated within a video file.)
using the plurality of encoded regions (Fig. 1, Paragraph [0246] - WANG discloses content preparation device 20 may then provide the first packed region to video encoder 28, to cause video encoder 28 to encode the first packed region (206). Paragraph [0247] - WANG further discloses content preparation device 20 provides the non-overlapping portion of the second packed region to video encoder 28, to cause video encoder 28 to encode the second packed region, excluding the overlap with the first packed region.)
and metadata corresponding to the plurality of regions (Fig. 6, Paragraph [0022] - WANG discloses a Movie box (“moov”) contains the metadata for the continuous media streams present in the file, each one represented in the file as a track. Paragraph [0243] - WANG further discloses video file 150 may further include a region-wise packing box (RWPB) including information as discussed above, e.g., within MOOV box 154. The RWPB may include an RWPB struct that defines locations of packed regions, and corresponding projected regions in a spherical video projection.).
Regarding claim 2, WANG teaches the one or more processors of claim 1,
WANG further teaches wherein the one or more circuits (Fig. 1, Paragraph [0103] - WANG discloses video encoder 28, video decoder 48, audio encoder 26, audio decoder 46, encapsulation unit 30, retrieval unit 52, and decapsulation unit 50 each may be implemented as any of a variety of suitable processing circuitry, as applicable, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic circuitry, software, hardware, firmware or any combinations thereof. See also Paragraph [0257].) are to:
generate the metadata to include the respective location of each of the plurality of regions within the image (Fig. 6, Paragraph [0022] - WANG discloses a Movie box (“moov”) contains the metadata for the continuous media streams present in the file, each one represented in the file as a track. Paragraph [0243] - WANG further discloses video file 150 may further include a region-wise packing box (RWPB) including information as discussed above, e.g., within MOOV box 154. The RWPB may include an RWPB struct that defines locations of packed regions, and corresponding projected regions in a spherical video projection.).
Regarding claim 4, WANG teaches the one or more processors of claim 1,
WANG further teaches wherein the one or more circuits (Fig. 1, Paragraph [0103] - WANG discloses video encoder 28, video decoder 48, audio encoder 26, audio decoder 46, encapsulation unit 30, retrieval unit 52, and decapsulation unit 50 each may be implemented as any of a variety of suitable processing circuitry, as applicable, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic circuitry, software, hardware, firmware or any combinations thereof. See also Paragraph [0257].) are to:
generate a header for the media package to include the metadata (Fig. 6, Paragraph [0022] - WANG discloses a Movie box (“moov”) contains the metadata for the continuous media streams present in the file, each one represented in the file as a track. Paragraph [0232] - WANG discloses MOOV box 154, in the example of FIG. 6, includes movie header (MVHD) box 156, track (TRAK) box 158, and one or more movie extends (MVEX) boxes 160. In general, MVHD box 156 may describe general characteristics of video file 150.)
corresponding to the plurality of regions (Fig. 6, Paragraph [0243] - WANG discloses video file 150 may further include a region-wise packing box (RWPB) including information as discussed above, e.g., within MOOV box 154. The RWPB may include an RWPB struct that defines locations of packed regions, and corresponding projected regions in a spherical video projection.).
Regarding claim 7, WANG teaches the one or more processors of claim 1,
WANG further teaches wherein each region of the plurality of regions comprises a different size (Fig. 3, Paragraph [0132] - WANG discloses FIG. 3 is a conceptual diagram illustrating two examples of region-wise packing (RWP) for OMAF. OMAF specifies a mechanism called region-wise packing (RWP). RWP enables manipulations (resize, reposition, rotation, and mirroring) of any rectangular region of a projected picture.).
Regarding claim 8, WANG teaches the one or more processors of claim 1,
WANG further teaches wherein the one or more circuits (Fig. 1, Paragraph [0103] - WANG discloses video encoder 28, video decoder 48, audio encoder 26, audio decoder 46, encapsulation unit 30, retrieval unit 52, and decapsulation unit 50 each may be implemented as any of a variety of suitable processing circuitry, as applicable, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic circuitry, software, hardware, firmware or any combinations thereof. See also Paragraph [0257].) are to:
encode a first region of the plurality of regions using a first set of encoding parameters (Fig. 1, Paragraph [0087] - WANG discloses video encoder 28 may encode video data of multimedia content in a variety of ways, to produce different representations of the multimedia content at various bitrates and with various characteristics, such as pixel resolutions, frame rates, conformance to various coding standards, conformance to various profiles and/or levels of profiles for various coding standards, representations having one or multiple views (e.g., for two-dimensional or three-dimensional playback), or other such characteristics. A representation, as used in this disclosure, may comprise one of audio data, video data, text data (e.g., for closed captions), or other such data.);
and encode a second region of the plurality of regions using a second set of encoding parameters (Fig. 1, Paragraph [0087] - WANG discloses video encoder 28 may encode video data of multimedia content in a variety of ways, to produce different representations of the multimedia content at various bitrates and with various characteristics, such as pixel resolutions, frame rates, conformance to various coding standards, conformance to various profiles and/or levels of profiles for various coding standards, representations having one or multiple views (e.g., for two-dimensional or three-dimensional playback), or other such characteristics. A representation, as used in this disclosure, may comprise one of audio data, video data, text data (e.g., for closed captions), or other such data.).
Regarding claim 10, WANG teaches a system (Fig. 1, #10 called system, Paragraph [0075] - WANG discloses FIG. 1 is a block diagram illustrating an example system 10 that implements techniques for streaming media data over a network.), comprising:
one or more processors (Fig. 1, Paragraph [0103] - WANG discloses video encoder 28, video decoder 48, audio encoder 26, audio decoder 46, encapsulation unit 30, retrieval unit 52, and decapsulation unit 50 each may be implemented as any of a variety of suitable processing circuitry, as applicable, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic circuitry, software, hardware, firmware or any combinations thereof. See also Paragraph [0257].) to:
extract at least a plurality of encoded regions from a media package (Fig. 1, Paragraph [0111] - WANG discloses decapsulation unit 50 may decapsulate a elements of a video file into constituent PES streams, depacketize the PES streams to retrieve encoded data, and send the encoded data to either audio decoder 46 or video decoder 48, depending on whether the encoded data is part of an audio or video stream.);
generate a plurality of regions of an image by decoding the plurality of encoded regions (Fig. 1, Paragraph [0250] - WANG discloses client device 40 may decode video data of media content. Client device 40 may then determine a first packed region of the decoded video data of the media content (250). Paragraph [0252] - WANG discloses client device 40 may then determine a second packed region of the decoded video data of the media content (256).);
and generate the image using at least the plurality of regions (Fig. 1, Paragraph [0111] - WANG discloses video decoder 48 decodes encoded video data and sends the decoded video data, which may include a plurality of views of a stream, to video output 44. See also Fig. 8, Paragraphs [0250-0253].).
Regarding claim 12, WANG teaches the system of claim 10,
WANG further teaches wherein the one or more processors (Fig. 1, Paragraph [0103] - WANG discloses video encoder 28, video decoder 48, audio encoder 26, audio decoder 46, encapsulation unit 30, retrieval unit 52, and decapsulation unit 50 each may be implemented as any of a variety of suitable processing circuitry, as applicable, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic circuitry, software, hardware, firmware or any combinations thereof. See also Paragraph [0257].) are to:
parse a header of the media package to identify metadata corresponding to the plurality of encoded regions (Fig. 6, Paragraph [0022] - WANG discloses a Movie box (“moov”) contains the metadata for the continuous media streams present in the file, each one represented in the file as a track. Paragraph [0232] - WANG discloses MOOV box 154, in the example of FIG. 6, includes movie header (MVHD) box 156, track (TRAK) box 158, and one or more movie extends (MVEX) boxes 160. In general, MVHD box 156 may describe general characteristics of video file 150. Paragraph [0243] - WANG discloses video file 150 may further include a region-wise packing box (RWPB) including information as discussed above, e.g., within MOOV box 154. Paragraph [0250] - WANG discloses client device 40 may receive a region-wise packing box (RWPB) including information as discussed above representing positions of the first packed region and a second packed region of the decoded video data of the media content.).
Regarding claim 13, WANG teaches the system of claim 10,
WANG further teaches wherein the one or more processors (Fig. 1, Paragraph [0103] - WANG discloses video encoder 28, video decoder 48, audio encoder 26, audio decoder 46, encapsulation unit 30, retrieval unit 52, and decapsulation unit 50 each may be implemented as any of a variety of suitable processing circuitry, as applicable, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic circuitry, software, hardware, firmware or any combinations thereof. See also Paragraph [0257].) are to:
determine, based on metadata corresponding to the plurality of encoded regions (Fig. 6, Paragraph [0022] - WANG discloses a Movie box (“moov”) contains the metadata for the continuous media streams present in the file, each one represented in the file as a track. Paragraph [0232] - WANG discloses MOOV box 154, in the example of FIG. 6, includes movie header (MVHD) box 156, track (TRAK) box 158, and one or more movie extends (MVEX) boxes 160. Paragraph [0243] - WANG further discloses video file 150 may further include a region-wise packing box (RWPB) including information as discussed above, e.g., within MOOV box 154. The RWPB may include an RWPB struct that defines locations of packed regions, and corresponding projected regions in a spherical video projection. See also Paragraph [0229].),
one or more offsets for the plurality of encoded regions in the media package (Fig. 5, Paragraph [0225] - WANG discloses header data 126, when present, may describe characteristics of segments 128, e.g., temporal locations of random access points (RAPs, also referred to as stream access points (SAPs)), which of segments 128 includes random access points, byte offsets to random access points within segments 128, uniform resource locators (URLs) of segments 128, or other aspects of segments 128. See also Fig. 6, Paragraph [0239].).
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 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.
Claims 3, 6, 14, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over WANG (US 20190020880 A1), hereinafter referenced as WANG in view of AHMAD (US 20240153146 A1), hereinafter referenced as AHMAD.
Regarding claim 3, WANG teaches the one or more processors of claim 1,
WANG further teaches wherein the one or more circuits (Fig. 1, Paragraph [0103] - WANG discloses video encoder 28, video decoder 48, audio encoder 26, audio decoder 46, encapsulation unit 30, retrieval unit 52, and decapsulation unit 50 each may be implemented as any of a variety of suitable processing circuitry, as applicable, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic circuitry, software, hardware, firmware or any combinations thereof. See also Paragraph [0257].) are to:
Although WANG teaches generate the media package (Fig. 1, Paragraph [0081] - WANG discloses video encoder 28 produces a stream of encoded video data. An elementary stream is a single, digitally coded (possibly compressed) component of a representation. For example, the coded video or audio part of the representation can be an elementary stream. An elementary stream may be converted into a packetized elementary stream (PES) before being encapsulated within a video file.),
WANG fails to explicitly teach generate the media package by concatenating each of the plurality of encoded regions.
However, AHMAD explicitly teaches generate the media package by concatenating each of the plurality of encoded regions (Fig. 7, Paragraph [0024] - AHMAD discloses encoder can concatenate or combine the image and the data matrix to generate a cover image with the data matrix embedded into a color channel (e.g., red-green-blue (RGB) channel) of the original image. Paragraph [0084] - AHMAD further discloses encoded image 725 can be formed using the set of image segments 710. Each image segment 710 can be encoded with the data matrix 720.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date the claimed invention was made to combine the teachings of WANG of having one or more processors comprising: one or more circuits to: extract a plurality of regions from an image to be encoded using an image encoding process; generate a plurality of encoded regions by encoding each of the plurality of regions using the image encoding process; and generate a media package using the plurality of encoded regions and metadata corresponding to the plurality of regions; with the teachings of AHMAD of having generate the media package by concatenating each of the plurality of encoded regions.
Wherein WANG’s one or more processors wherein the one or more circuits are to: generate the media package by concatenating each of the plurality of encoded regions.
The motivation behind this modification would have been to provide an enhanced method of media processing that improves coding efficiency and visual quality, since both WANG and AHMAD relate to methods and systems for processing media content, wherein WANG relates to storage and transport of encoded video data; infrequently changing information need not to be repeated for each sequence or picture, hence coding efficiency may be improved, and AHMAD discloses systems and methods to encode images into messages and decode messages from images; a data processing system can embed a data matrix code from the secret message into a color channel of a cover image using a neural network-based encoder-decoder model to achieve high visual quality and security. Please see WANG (US 20190020880 A1), Paragraph [0082, 0089], and AHMAD (US 20240153146 A1), Paragraph [0023].
Regarding claim 6, WANG teaches the one or more processors of claim 1,
WANG fails to explicitly teach wherein the media package comprises one of a Joint Photographic Experts Group (JPEG) file, a portable network graphics (PNG) file, a tagged image file format (TIFF) file, or a WEBP file.
However, AHMAD explicitly teaches wherein the media package comprises one of a Joint Photographic Experts Group (JPEG) file (Fig. 5, Paragraph [0059] - AHMAD discloses encoded image 515 can correspond to at least one image file in any format, such as a bitmap (BMP), a Joint Photographic Experts Group (JPEG) format, a Graphics Interchange Format (GIF), Portable Network Graphics (PNG) format, Scalable Vector Graphics (SVG) format, or a Tag Image File Format (TIFF), among others.),
a portable network graphics (PNG) file (Fig. 5, Paragraph [0059] - AHMAD discloses encoded image 515 can correspond to at least one image file in any format, such as a bitmap (BMP), a Joint Photographic Experts Group (JPEG) format, a Graphics Interchange Format (GIF), Portable Network Graphics (PNG) format, Scalable Vector Graphics (SVG) format, or a Tag Image File Format (TIFF), among others.),
a tagged image file format (TIFF) file (Fig. 5, Paragraph [0059] - AHMAD discloses encoded image 515 can correspond to at least one image file in any format, such as a bitmap (BMP), a Joint Photographic Experts Group (JPEG) format, a Graphics Interchange Format (GIF), Portable Network Graphics (PNG) format, Scalable Vector Graphics (SVG) format, or a Tag Image File Format (TIFF), among others.),
or a WEBP file (Fig. 5, Paragraph [0059] - AHMAD discloses encoded image 515 can correspond to at least one image file in any format [wherein any format can include WEBP file], such as a bitmap (BMP), a Joint Photographic Experts Group (JPEG) format, a Graphics Interchange Format (GIF), Portable Network Graphics (PNG) format, Scalable Vector Graphics (SVG) format, or a Tag Image File Format (TIFF), among others.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date the claimed invention was made to combine the teachings of WANG of having one or more processors comprising: one or more circuits to: extract a plurality of regions from an image to be encoded using an image encoding process; generate a plurality of encoded regions by encoding each of the plurality of regions using the image encoding process; and generate a media package using the plurality of encoded regions and metadata corresponding to the plurality of regions; with the teachings of AHMAD of having wherein the media package comprises one of a Joint Photographic Experts Group (JPEG) file, a portable network graphics (PNG) file, a tagged image file format (TIFF) file, or a WEBP file.
Wherein WANG’s one or more processors wherein the media package comprises one of a Joint Photographic Experts Group (JPEG) file, a portable network graphics (PNG) file, a tagged image file format (TIFF) file, or a WEBP file.
The motivation behind this modification would have been to provide an enhanced method of media processing that improves coding efficiency and visual quality, since both WANG and AHMAD relate to methods and systems for processing media content, wherein WANG relates to storage and transport of encoded video data; infrequently changing information need not to be repeated for each sequence or picture, hence coding efficiency may be improved, and AHMAD discloses systems and methods to encode images into messages and decode messages from images; a data processing system can embed a data matrix code from the secret message into a color channel of a cover image using a neural network-based encoder-decoder model to achieve high visual quality and security. Please see WANG (US 20190020880 A1), Paragraph [0082, 0089], and AHMAD (US 20240153146 A1), Paragraph [0023].
Regarding claim 14, WANG teaches the system of claim 10,
WANG fails to explicitly teach wherein the media package comprises an image file, wherein each of the plurality of encoded regions is concatenated and stored as image data in the image file.
However, AHMAD explicitly teaches wherein the media package comprises an image file (Fig. 7, Paragraph [0083] - AHMAD discloses the model applier 130 can aggregate, join, or otherwise combine the original image 705 (or each image segment 710) and the data matrix 720 to output, produce, or otherwise generate at least one input to feed to the encoder 150. The model applier 130 can also gather, combine, or aggregate outputs from applying each image segment 710 to form or generate the encoded image 725. Each output can correspond to a respective input image segment 710, and the encoded image 725 can be formed by the model applier 130 using the combination of the outputs. Paragraph [0086] - AHMAD further discloses the model applier 130 can store and maintain the encoded image 725 [wherein encoded image 725 is the media package] on the database 160 (e.g., in the form of a file or data structures).),
wherein each of the plurality of encoded regions is concatenated and stored as image data in the image file (Fig. 7, Paragraph [0024] - AHMAD discloses encoder can concatenate or combine the image and the data matrix to generate a cover image with the data matrix embedded into a color channel (e.g., red-green-blue (RGB) channel) of the original image. Paragraph [0084] - AHMAD further discloses encoded image 725 can be formed using the set of image segments 710. Each image segment 710 can be encoded with the data matrix 720. Paragraph [0086] - AHMAD further discloses the model applier 130 can store and maintain the encoded image 725 on the database 160 (e.g., in the form of a file or data structures).).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date the claimed invention was made to combine the teachings of WANG of having a system, comprising: one or more processors to: extract at least a plurality of encoded regions from a media package; generate a plurality of regions of an image by decoding the plurality of encoded regions; and generate the image using at least the plurality of regions, with the teachings of AHMAD of having wherein the media package comprises an image file, wherein each of the plurality of encoded regions is concatenated and stored as image data in the image file.
Wherein WANG’s system wherein the media package comprises an image file, wherein each of the plurality of encoded regions is concatenated and stored as image data in the image file.
The motivation behind this modification would have been to provide an enhanced system for media processing that improves coding efficiency and visual quality, since both WANG and AHMAD relate to methods and systems for processing media content, wherein WANG relates to storage and transport of encoded video data; infrequently changing information need not to be repeated for each sequence or picture, hence coding efficiency may be improved, and AHMAD discloses systems and methods to encode images into messages and decode messages from images; a data processing system can embed a data matrix code from the secret message into a color channel of a cover image using a neural network-based encoder-decoder model to achieve high visual quality and security. Please see WANG (US 20190020880 A1), Paragraph [0082, 0089], and AHMAD (US 20240153146 A1), Paragraph [0023].
Regarding claim 18, WANG teaches a method (Fig. 7, Paragraph [0244] - WANG discloses FIG. 7 is a flowchart illustrating an example method of generating video data according to the techniques of this disclosure.), comprising:
obtaining, using one or more processors (Fig. 1, Paragraph [0257] - WANG discloses instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry.),
a plurality of regions from an image to be encoded (Fig. 7, Paragraph [0245] - WANG discloses content preparation device 20 may determine a first projected region of the media content (200). Paragraph [0247] - WANG discloses content preparation device 20 may then determine a second projected region from the received media content (206). Fig. 1, Paragraph [0082].);
applying, using the one or more processors (Fig. 1, Paragraph [0257]),
Although WANG further teaches a plurality of levels of compression to the plurality of regions to generate a plurality of encoded regions (Fig. 1, Paragraph [0087] - WANG discloses video encoder 28 may encode video data of multimedia content in a variety of ways, to produce different representations of the multimedia content at various bitrates [wherein producing representations at various bitrates is applying a plurality of levels of compression] and with various characteristics, such as pixel resolutions, frame rates, conformance to various coding standards, conformance to various profiles and/or levels of profiles for various coding standards, representations having one or multiple views (e.g., for two-dimensional or three-dimensional playback), or other such characteristics. See also Paragraph [0082].);
WANG fails to explicitly teach and concatenating, using the one or more processors, the plurality of encoded regions to generate a media package.
However, AHMAD explicitly teaches and concatenating, using the one or more processors (Fig. 14, #1410 called processor, Paragraph [0114], see also Paragraph [0029].),
the plurality of encoded regions to generate a media package (Fig. 7, Paragraph [0024] - AHMAD discloses encoder can concatenate or combine the image and the data matrix to generate a cover image with the data matrix embedded into a color channel (e.g., red-green-blue (RGB) channel) of the original image. Paragraph [0084] - AHMAD further discloses encoded image 725 can be formed using the set of image segments 710. Each image segment 710 can be encoded with the data matrix 720.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date the claimed invention was made to combine the teachings of WANG of having a method, comprising: obtaining, using one or more processors, a plurality of regions from an image to be encoded; applying, using the one or more processors, a plurality of levels of compression to the plurality of regions to generate a plurality of encoded regions; with the teachings of AHMAD of having and concatenating, using the one or more processors, the plurality of encoded regions to generate a media package.
Wherein WANG’s method wherein having and concatenating, using the one or more processors, the plurality of encoded regions to generate a media package.
The motivation behind this modification would have been to provide an enhanced method of media processing that improves coding efficiency and visual quality, since both WANG and AHMAD relate to methods and systems for processing media content, wherein WANG relates to storage and transport of encoded video data; infrequently changing information need not to be repeated for each sequence or picture, hence coding efficiency may be improved, and AHMAD discloses systems and methods to encode images into messages and decode messages from images; a data processing system can embed a data matrix code from the secret message into a color channel of a cover image using a neural network-based encoder-decoder model to achieve high visual quality and security. Please see WANG (US 20190020880 A1), Paragraph [0082, 0089], and AHMAD (US 20240153146 A1), Paragraph [0023].
Regarding claim 19, WANG in view of AHMAD teach the method of claim 18,
WANG further teaches further comprising generating, using the one or more processors (Fig. 1, Paragraph [0257] - WANG discloses instructions may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, application specific integrated circuits (ASICs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry.),
metadata corresponding to the plurality of regions (Fig. 6, Paragraph [0022] - WANG discloses a Movie box (“moov”) contains the metadata for the continuous media streams present in the file, each one represented in the file as a track. Paragraph [0243] - WANG further discloses video file 150 may further include a region-wise packing box (RWPB) including information as discussed above, e.g., within MOOV box 154. The RWPB may include an RWPB struct that defines locations of packed regions, and corresponding projected regions in a spherical video projection.),
the metadata including the respective location of each of the plurality of regions within the image (Fig. 6, Paragraph [0022] - WANG discloses a Movie box (“moov”) contains the metadata for the continuous media streams present in the file, each one represented in the file as a track. Paragraph [0243] - WANG further discloses video file 150 may further include a region-wise packing box (RWPB) including information as discussed above, e.g., within MOOV box 154. The RWPB may include an RWPB struct that defines locations of packed regions, and corresponding projected regions in a spherical video projection.).
Regarding claim 20, WANG in view of AHMAD teach the method of claim 19,
WANG further teaches wherein the media package is generated (Fig. 1, Paragraph [0081] - WANG discloses video encoder 28 produces a stream of encoded video data. An elementary stream is a single, digitally coded (possibly compressed) component of a representation. For example, the coded video or audio part of the representation can be an elementary stream. An elementary stream may be converted into a packetized elementary stream (PES) before being encapsulated within a video file.)
using at least the metadata corresponding to the plurality of regions (Fig. 6, Paragraph [0022] - WANG discloses a Movie box (“moov”) contains the metadata for the continuous media streams present in the file, each one represented in the file as a track. Paragraph [0243] - WANG further discloses video file 150 may further include a region-wise packing box (RWPB) including information as discussed above, e.g., within MOOV box 154. The RWPB may include an RWPB struct that defines locations of packed regions, and corresponding projected regions in a spherical video projection.).
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over WANG (US 20190020880 A1), hereinafter referenced as WANG in view of HINDS (US 20250119588 A1), hereinafter referenced as HINDS.
Regarding claim 5, WANG teaches the one or more processors of claim 4,
WANG fails to explicitly teach wherein the metadata is provided as exchangeable image file format (EXIF) data in the header of the media package.
However, HINDS explicitly teaches wherein the metadata is provided as exchangeable image file format (EXIF) data in the header of the media package (Fig. 5, Paragraph [0083] - HINDS discloses a simplified syntax diagram of a NAL unit that contains a prefix or suffix SEI message 520. This syntax is a container format for multiple SEI messages that can be carried in one NAL unit. As other NAL units, SEI NAL units start with a NAL unit header 521. Paragraph [0087] - HINDS further discloses SEI messages and syntaxes disclosed herein may carry payloads from popular image metadata formats, i.e., Exchangeable Image File (EXIF) metadata, JPEG File Interchange Format (JFIF), and Extensible Metadata Platform (XMP), etc.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date the claimed invention was made to combine the teachings of WANG of having one or more processors comprising: one or more circuits to: extract a plurality of regions from an image to be encoded using an image encoding process; generate a plurality of encoded regions by encoding each of the plurality of regions using the image encoding process; and generate a media package using the plurality of encoded regions and metadata corresponding to the plurality of regions; with the teachings of HINDS of having wherein the metadata is provided as exchangeable image file format (EXIF) data in the header of the media package.
Wherein WANG’s one or more processors wherein the metadata is provided as exchangeable image file format (EXIF) data in the header of the media package.
The motivation behind this modification would have been to provide an enhanced method of media processing that improves coding efficiency and allows for various metadata formats, since both WANG and HINDS relate to methods and systems for processing media content, wherein WANG relates to storage and transport of encoded video data; infrequently changing information need not to be repeated for each sequence or picture, hence coding efficiency may be improved, and HINDS relates to video coding and decoding wherein SEI messages to enable the carriage of popular image metadata formats within coded video streams. Please see WANG (US 20190020880 A1), Paragraph [0082, 0089], and HINDS (US 20250119588 A1), Paragraph [0087].
Claims 9 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over WANG (US 20190020880 A1), hereinafter referenced as WANG in view of XIONG (US 20240161436 A1), hereinafter referenced as XIONG, in further view of AHMAD (US 20240153146 A1), hereinafter referenced as AHMAD, in further view of NITZAN (US 20250308109 A1), hereinafter referenced as NITZAN.
Regarding claim 9, WANG teaches the one or more processors of claim 1,
WANG further teaches wherein the one or more processors (Fig. 1, Paragraph [0103] - WANG discloses video encoder 28, video decoder 48, audio encoder 26, audio decoder 46, encapsulation unit 30, retrieval unit 52, and decapsulation unit 50 each may be implemented as any of a variety of suitable processing circuitry, as applicable, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic circuitry, software, hardware, firmware or any combinations thereof. See also Paragraph [0257].) are comprised in at least one of:
a system for presenting at least one of virtual reality content, augmented reality content, or mixed reality content (Fig. 1, Paragraph [0245] - WANG discloses content preparation device receives media content, including video data from video source 24. The video data may represent spherical video data, e.g., for use in VR, augmented reality, or the like. See also Paragraph [0027].);
WANG fails to explicitly teach a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system implemented using a robot;
However, XIONG explicitly teaches control system for an autonomous or semi-autonomous machine (Fig. 1, Paragraph [0028] - XIONG discloses the autonomous system (116) includes one or more actuators (108). An actuator is hardware and/or software that is configured to control one or more physical parts of the autonomous system based on a control signal from the virtual driver (102). In one or more embodiments, the control signal specifies an action for the autonomous system (e.g., turn on the blinker, apply breaks by a defined amount, apply accelerator by a defined amount, turn the steering wheel or tires by a defined amount, etc.).);
a perception system for an autonomous or semi-autonomous machine (Fig. 1, Paragraph [0022] - XIONG discloses one or more embodiments may be used to generate and manage LiDAR used by autonomous systems or in the testing and training of autonomous systems. Turning to the Figures, FIGS. 1 and 2 show example diagrams of the autonomous system and virtual driver. The autonomous system (116) may be completely autonomous or semi-autonomous.);
a system for performing simulation operations (Fig. 2, Paragraph [0029] - XIONG discloses as shown in FIG. 2, a simulator (200) is configured to train and test a virtual driver (102) of an autonomous system. XIONG further discloses the simulator may be a unified, modular, mixed-reality, closed-loop simulator for autonomous systems. The simulator (200) is a configurable simulation framework that enables not only evaluation of different autonomy components of the virtual driver (102) in isolation, but also as a complete system in a closed-loop manner.);
a system for performing digital twin operations (Fig. 2, Paragraph [0029] - XIONG discloses as shown in FIG. 2, a simulator (200) is configured to train and test a virtual driver (102) of an autonomous system. The simulator reconstructs “digital twins” of real-world scenarios automatically, enabling accurate evaluation of the virtual driver at scale. The simulator (200) creates the simulated environment (204) which is a virtual world in which the virtual driver (102) is a player in the virtual world.);
a system implemented using a robot (Fig. 1, Paragraph [0022] - XIONG discloses one or more embodiments may be used to generate and manage LiDAR used by autonomous systems or in the testing and training of autonomous systems. Turning to the Figures, FIGS. 1 and 2 show example diagrams of the autonomous system and virtual driver. The autonomous system (116) may be completely autonomous or semi-autonomous. Examples of autonomous systems include self-driving vehicles (e.g., self-driving trucks and cars), drones, airplanes, robots, etc.);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date the claimed invention was made to combine the teachings of WANG of having one or more processors comprising: one or more circuits to: extract a plurality of regions from an image to be encoded using an image encoding process; generate a plurality of encoded regions by encoding each of the plurality of regions using the image encoding process; and generate a media package using the plurality of encoded regions and metadata corresponding to the plurality of regions; with the teachings of XIONG of having a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system implemented using a robot.
Wherein WANG’s one or more processors wherein the one or more processors are comprised in at least one of: a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system for performing light transport simulation; a system for performing collaborative content creation for 3D assets; a system for performing deep learning operations; a system implemented using an edge device; a system implemented using a robot; a system for performing conversational AI operations; a system for performing generative AI operations using a large language model (LLM); a system for performing generative AI operations using a small language model (SLM); a system for performing one or more conversational AI operations; a system for presenting at least one of virtual reality content, augmented reality content, or mixed reality content; a system for generating synthetic data; a system incorporating one or more virtual machines (VMs); a system implemented at least partially in a data center; or a system implemented at least partially using cloud computing resources.
The motivation behind this modification would have been to provide an enhanced method of media processing that improves coding efficiency and is robust to noise, since both WANG and XIONG relate to methods and systems for encoding and decoding computer graphics data, wherein WANG relates to storage and transport of encoded video data; infrequently changing information need not to be repeated for each sequence or picture, hence coding efficiency may be improved, and XIONG relates to generating a three-dimensional (3D) LiDAR image from LiDAR input data, encoding, by an encoder model, the 3D LiDAR image to a continuous embedding in continuous space, and performing, using a code map, a vector quantization of the continuous embedding to generate a discrete embedding; the transformation of the vector quantization using the code map creates a compact, discrete representation that encodes the LiDAR data's geometric structure, is robust to noise, and is easy to manipulate. Please see WANG (US 20190020880 A1), Paragraph [0082, 0089], and XIONG (US 20240161436 A1), Paragraph [0021, 0071].
WANG in view of XIONG fail to explicitly teach a system for performing deep learning operations; a system incorporating one or more virtual machines (VMs);
However, AHMAD explicitly teaches a system for performing deep learning operations (Fig. 1, Paragraph [0055] – AHMAD discloses encoder 150 can use the convolution blocks 405 and the deconvolution blocks 410 arranged across a variety of layers to improve the precision in learning shallow and deep features.);
a system incorporating one or more virtual machines (VMs) (Fig. 1, Paragraph [0122] – AHMAD discloses the apparatus can also include, in addition to hardware, code that creates an execution environment for the computer program in question, e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, a cross-platform runtime environment, a virtual machine, or a combination of one or more of them.);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date the claimed invention was made to combine the teachings of WANG of having one or more processors comprising: one or more circuits to: extract a plurality of regions from an image to be encoded using an image encoding process; generate a plurality of encoded regions by encoding each of the plurality of regions using the image encoding process; and generate a media package using the plurality of encoded regions and metadata corresponding to the plurality of regions; with the teachings of AHMAD of having a system for performing deep learning operations; a system incorporating one or more virtual machines (VMs).
Wherein WANG’s one or more processors wherein the one or more processors are comprised in at least one of: a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system for performing light transport simulation; a system for performing collaborative content creation for 3D assets; a system for performing deep learning operations; a system implemented using an edge device; a system implemented using a robot; a system for performing conversational AI operations; a system for performing generative AI operations using a large language model (LLM); a system for performing generative AI operations using a small language model (SLM); a system for performing one or more conversational AI operations; a system for presenting at least one of virtual reality content, augmented reality content, or mixed reality content; a system for generating synthetic data; a system incorporating one or more virtual machines (VMs); a system implemented at least partially in a data center; or a system implemented at least partially using cloud computing resources.
The motivation behind this modification would have been to provide an enhanced method of media processing that improves coding efficiency and visual quality, since both WANG and AHMAD relate to methods and systems for processing media content, wherein WANG relates to storage and transport of encoded video data; infrequently changing information need not to be repeated for each sequence or picture, hence coding efficiency may be improved, and AHMAD discloses systems and methods to encode images into messages and decode messages from images; a data processing system can embed a data matrix code from the secret message into a color channel of a cover image using a neural network-based encoder-decoder model to achieve high visual quality and security. Please see WANG (US 20190020880 A1), Paragraph [0082, 0089], and AHMAD (US 20240153146 A1), Paragraph [0023].
WANG in view of XIONG, further in view of AHMAD fail to explicitly teach a system for generating synthetic data; or a system implemented at least partially using cloud computing resources.
However, NITZAN explicitly teaches a system for generating synthetic data (Fig. 1, Paragraph [0083] – NITZAN discloses local refinement generative system 102 also includes a data storage manager 910 (that comprises a non-transitory computer memory) that stores and maintains data associated with generating synthetic digital images.);
or a system implemented at least partially using cloud computing resources (Fig. 1, Paragraph [0106] – NITZAN discloses embodiments of the present disclosure can also be implemented in cloud computing environments. In this description, “cloud computing” is defined as a model for enabling on-demand network access to a shared pool of configurable computing resources.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date the claimed invention was made to combine the teachings of WANG of having one or more processors comprising: one or more circuits to: extract a plurality of regions from an image to be encoded using an image encoding process; generate a plurality of encoded regions by encoding each of the plurality of regions using the image encoding process; and generate a media package using the plurality of encoded regions and metadata corresponding to the plurality of regions; with the teachings of NITZAN of having a system for generating synthetic data; or a system implemented at least partially using cloud computing resources.
Wherein WANG’s one or more processors wherein the one or more processors are comprised in at least one of: a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system for performing light transport simulation; a system for performing collaborative content creation for 3D assets; a system for performing deep learning operations; a system implemented using an edge device; a system implemented using a robot; a system for performing conversational AI operations; a system for performing generative AI operations using a large language model (LLM); a system for performing generative AI operations using a small language model (SLM); a system for performing one or more conversational AI operations; a system for presenting at least one of virtual reality content, augmented reality content, or mixed reality content; a system for generating synthetic data; a system incorporating one or more virtual machines (VMs); a system implemented at least partially in a data center; or a system implemented at least partially using cloud computing resources.
The motivation behind this modification would have been to provide an enhanced method of media processing that improves coding efficiency and accuracy, since both WANG and NITZAN relate to methods and systems for processing media content, wherein WANG relates to storage and transport of encoded video data; infrequently changing information need not to be repeated for each sequence or picture, hence coding efficiency may be improved, and NITZAN discloses a local refinement generative system that edits digital images with a generative neural network via local refinement of features corresponding to specific portions of the digital images; the local refinement generative system provides high accuracy in a computing system that generates/edits digital images in addition to providing speed and efficiency. Please see WANG (US 20190020880 A1), Paragraph [0082, 0089], and NITZAN (US 20250308109 A1), Paragraph [0022].
Regarding claim 17, WANG teaches the system of claim 10,
WANG further teaches wherein the one or more processors (Fig. 1, Paragraph [0103] - WANG discloses video encoder 28, video decoder 48, audio encoder 26, audio decoder 46, encapsulation unit 30, retrieval unit 52, and decapsulation unit 50 each may be implemented as any of a variety of suitable processing circuitry, as applicable, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic circuitry, software, hardware, firmware or any combinations thereof. See also Paragraph [0257].) are comprised in at least one of:
a system for performing one or more conversational AI operations; a system for presenting at least one of virtual reality content, augmented reality content, or mixed reality content (Fig. 1, Paragraph [0245] - WANG discloses content preparation device receives media content, including video data from video source 24. The video data may represent spherical video data, e.g., for use in VR, augmented reality, or the like. See also Paragraph [0027].);
WANG fails to explicitly teach a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system implemented using a robot;
However, XIONG explicitly teaches a control system for an autonomous or semi-autonomous machine (Fig. 1, Paragraph [0028] - XIONG discloses the autonomous system (116) includes one or more actuators (108). An actuator is hardware and/or software that is configured to control one or more physical parts of the autonomous system based on a control signal from the virtual driver (102). In one or more embodiments, the control signal specifies an action for the autonomous system (e.g., turn on the blinker, apply breaks by a defined amount, apply accelerator by a defined amount, turn the steering wheel or tires by a defined amount, etc.).);
a perception system for an autonomous or semi-autonomous machine (Fig. 1, Paragraph [0022] - XIONG discloses one or more embodiments may be used to generate and manage LiDAR used by autonomous systems or in the testing and training of autonomous systems. Turning to the Figures, FIGS. 1 and 2 show example diagrams of the autonomous system and virtual driver. The autonomous system (116) may be completely autonomous or semi-autonomous.);
a system for performing simulation operations (Fig. 2, Paragraph [0029] - XIONG discloses as shown in FIG. 2, a simulator (200) is configured to train and test a virtual driver (102) of an autonomous system. XIONG further discloses the simulator may be a unified, modular, mixed-reality, closed-loop simulator for autonomous systems. The simulator (200) is a configurable simulation framework that enables not only evaluation of different autonomy components of the virtual driver (102) in isolation, but also as a complete system in a closed-loop manner.);
a system for performing digital twin operations (Fig. 2, Paragraph [0029] - XIONG discloses as shown in FIG. 2, a simulator (200) is configured to train and test a virtual driver (102) of an autonomous system. The simulator reconstructs “digital twins” of real-world scenarios automatically, enabling accurate evaluation of the virtual driver at scale. The simulator (200) creates the simulated environment (204) which is a virtual world in which the virtual driver (102) is a player in the virtual world.);
a system implemented using a robot (Fig. 1, Paragraph [0022] - XIONG discloses one or more embodiments may be used to generate and manage LiDAR used by autonomous systems or in the testing and training of autonomous systems. Turning to the Figures, FIGS. 1 and 2 show example diagrams of the autonomous system and virtual driver.The autonomous system (116) may be completely autonomous or semi-autonomous. Examples of autonomous systems include self-driving vehicles (e.g., self-driving trucks and cars), drones, airplanes, robots, etc.);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date the claimed invention was made to combine the teachings of WANG of having a system, comprising: one or more processors to: extract at least a plurality of encoded regions from a media package; generate a plurality of regions of an image by decoding the plurality of encoded regions; and generate the image using at least the plurality of regions, with the teachings of XIONG of having a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system implemented using a robot.
Wherein WANG’s system wherein the one or more processors are comprised in at least one of: a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system for performing light transport simulation; a system for performing collaborative content creation for 3D assets; a system for performing deep learning operations; a system implemented using an edge device; a system implemented using a robot; a system for performing conversational AI operations; a system for performing generative AI operations using a large language model (LLM); a system for performing generative AI operations using a small language model (SLM); a system for performing one or more conversational AI operations; a system for presenting at least one of virtual reality content, augmented reality content, or mixed reality content; a system for generating synthetic data; a system incorporating one or more virtual machines (VMs); a system implemented at least partially in a data center; or a system implemented at least partially using cloud computing resources.
The motivation behind this modification would have been to provide an enhanced system for media processing that improves coding efficiency and is robust to noise, since both WANG and XIONG relate to methods and systems for encoding and decoding computer graphics data, wherein WANG relates to storage and transport of encoded video data; infrequently changing information need not to be repeated for each sequence or picture, hence coding efficiency may be improved, and XIONG relates to generating a three-dimensional (3D) LiDAR image from LiDAR input data, encoding, by an encoder model, the 3D LiDAR image to a continuous embedding in continuous space, and performing, using a code map, a vector quantization of the continuous embedding to generate a discrete embedding; the transformation of the vector quantization using the code map creates a compact, discrete representation that encodes the LiDAR data's geometric structure, is robust to noise, and is easy to manipulate. Please see WANG (US 20190020880 A1), Paragraph [0082, 0089], and XIONG (US 20240161436 A1), Paragraph [0021, 0071].
WANG in view of XIONG fail to explicitly teach a system for performing deep learning operations; a system incorporating one or more virtual machines (VMs);
However, AHMAD explicitly teaches a system for performing deep learning operations (Fig. 1, Paragraph [0055] – AHMAD discloses encoder 150 can use the convolution blocks 405 and the deconvolution blocks 410 arranged across a variety of layers to improve the precision in learning shallow and deep features.);
a system incorporating one or more virtual machines (VMs) (Fig. 1, Paragraph [0122] – AHMAD discloses the apparatus can also include, in addition to hardware, code that creates an execution environment for the computer program in question, e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, a cross-platform runtime environment, a virtual machine, or a combination of one or more of them.);
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date the claimed invention was made to combine the teachings of WANG of having a system, comprising: one or more processors to: extract at least a plurality of encoded regions from a media package; generate a plurality of regions of an image by decoding the plurality of encoded regions; and generate the image using at least the plurality of regions, with the teachings of AHMAD of having a system for performing deep learning operations; a system incorporating one or more virtual machines (VMs).
Wherein WANG’s system wherein the one or more processors are comprised in at least one of: a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system for performing light transport simulation; a system for performing collaborative content creation for 3D assets; a system for performing deep learning operations; a system implemented using an edge device; a system implemented using a robot; a system for performing conversational AI operations; a system for performing generative AI operations using a large language model (LLM); a system for performing generative AI operations using a small language model (SLM); a system for performing one or more conversational AI operations; a system for presenting at least one of virtual reality content, augmented reality content, or mixed reality content; a system for generating synthetic data; a system incorporating one or more virtual machines (VMs); a system implemented at least partially in a data center; or a system implemented at least partially using cloud computing resources.
The motivation behind this modification would have been to provide an enhanced method of media processing that improves coding efficiency and visual quality, since both WANG and AHMAD relate to methods and systems for processing media content, wherein WANG relates to storage and transport of encoded video data; infrequently changing information need not to be repeated for each sequence or picture, hence coding efficiency may be improved, and AHMAD discloses systems and methods to encode images into messages and decode messages from images; a data processing system can embed a data matrix code from the secret message into a color channel of a cover image using a neural network-based encoder-decoder model to achieve high visual quality and security. Please see WANG (US 20190020880 A1), Paragraph [0082, 0089], and AHMAD (US 20240153146 A1), Paragraph [0023].
WANG in view of XIONG, further in view of AHMAD fail to explicitly teach a system for generating synthetic data; or a system implemented at least partially using cloud computing resources.
However, NITZAN explicitly teaches a system for generating synthetic data (Fig. 1, Paragraph [0083] – NITZAN discloses local refinement generative system 102 also includes a data storage manager 910 (that comprises a non-transitory computer memory) that stores and maintains data associated with generating synthetic digital images.);
or a system implemented at least partially using cloud computing resources (Fig. 1, Paragraph [0106] – NITZAN discloses embodiments of the present disclosure can also be implemented in cloud computing environments. In this description, “cloud computing” is defined as a model for enabling on-demand network access to a shared pool of configurable computing resources.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date the claimed invention was made to combine the teachings of WANG of having a system, comprising: one or more processors to: extract at least a plurality of encoded regions from a media package; generate a plurality of regions of an image by decoding the plurality of encoded regions; and generate the image using at least the plurality of regions, with the teachings of NITZAN of having a system for generating synthetic data; or a system implemented at least partially using cloud computing resources.
Wherein WANG’s system wherein the one or more processors are comprised in at least one of: a control system for an autonomous or semi-autonomous machine; a perception system for an autonomous or semi-autonomous machine; a system for performing simulation operations; a system for performing digital twin operations; a system for performing light transport simulation; a system for performing collaborative content creation for 3D assets; a system for performing deep learning operations; a system implemented using an edge device; a system implemented using a robot; a system for performing conversational AI operations; a system for performing generative AI operations using a large language model (LLM); a system for performing generative AI operations using a small language model (SLM); a system for performing one or more conversational AI operations; a system for presenting at least one of virtual reality content, augmented reality content, or mixed reality content; a system for generating synthetic data; a system incorporating one or more virtual machines (VMs); a system implemented at least partially in a data center; or a system implemented at least partially using cloud computing resources.
The motivation behind this modification would have been to provide an enhanced method of media processing that improves coding efficiency and accuracy, since both WANG and NITZAN relate to methods and systems for processing media content, wherein WANG relates to storage and transport of encoded video data; infrequently changing information need not to be repeated for each sequence or picture, hence coding efficiency may be improved, and NITZAN discloses a local refinement generative system that edits digital images with a generative neural network via local refinement of features corresponding to specific portions of the digital images; the local refinement generative system provides high accuracy in a computing system that generates/edits digital images in addition to providing speed and efficiency. Please see WANG (US 20190020880 A1), Paragraph [0082, 0089], and NITZAN (US 20250308109 A1), Paragraph [0022].
Claims 11, 15, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over WANG (US 20190020880 A1), hereinafter referenced as WANG in view of DRUGEON (US 20260197505 A1), hereinafter referenced as DRUGEON.
Regarding claim 11, WANG teaches the system of claim 10,
Although WANG further teaches wherein the one or more processors (Fig. 1, Paragraph [0103] - WANG discloses video encoder 28, video decoder 48, audio encoder 26, audio decoder 46, encapsulation unit 30, retrieval unit 52, and decapsulation unit 50 each may be implemented as any of a variety of suitable processing circuitry, as applicable, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic circuitry, software, hardware, firmware or any combinations thereof. See also Paragraph [0257].) are to:
WANG fails to explicitly teach apply a filter to the image to remove an encoding artifact.
However, DRUGEON explicitly teaches apply a filter to the image to remove an encoding artifact (Fig. 22, Paragraph [0321] - DRUGEON discloses a least square error filter for removing compression artifacts is applied. For example, one filter selected from among a plurality of filters based on the direction and activity of local gradients is applied for each of 2×2 pixel sub-blocks in the current block.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date the claimed invention was made to combine the teachings of WANG of having a system, comprising: one or more processors to: extract at least a plurality of encoded regions from a media package; generate a plurality of regions of an image by decoding the plurality of encoded regions; and generate the image using at least the plurality of regions, with the teachings of DRUGEON of having apply a filter to the image to remove an encoding artifact.
Wherein WANG’s system wherein having apply a filter to the image to remove an encoding artifact.
The motivation behind this modification would have been to provide an enhanced system for media processing that improves coding efficiency and allows for various metadata formats, since both WANG and DRUGEON relate to methods and systems for processing media content, wherein WANG relates to storage and transport of encoded video data; infrequently changing information need not to be repeated for each sequence or picture, hence coding efficiency may be improved, and DRUGEON relates to video coding and decoding systems, components, and methods wherein an improvement in coding efficiency, an improvement in image quality, a reduction in the processing amount, and an improvement in processing efficiency can be achieved. Please see WANG (US 20190020880 A1), Paragraph [0082, 0089], and DRUGEON (US 20260197505 A1), Paragraph [0749].
Regarding claim 15, WANG teaches the system of claim 10,
Although WANG further teaches wherein the one or more processors (Fig. 1, Paragraph [0103] - WANG discloses video encoder 28, video decoder 48, audio encoder 26, audio decoder 46, encapsulation unit 30, retrieval unit 52, and decapsulation unit 50 each may be implemented as any of a variety of suitable processing circuitry, as applicable, such as one or more microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), discrete logic circuitry, software, hardware, firmware or any combinations thereof. See also Paragraph [0257].) are to:
WANG fails to explicitly teach decode a first encoded region of the plurality of encoded regions using a first set of decoding parameters; and decode a second encoded region of the plurality of encoded regions using a second set of decoding parameters.
However, DURGEON explicitly teaches decode a first encoded region of the plurality of encoded regions using a first set of decoding parameters (Fig. 2, Paragraph [0210] - DRUGEON discloses a picture may include a picture header and at least one slice. A picture header includes a coding parameter which decoder 200 refers to in order to decode the at least one slice. Paragraph [0227] - DRUGEON discloses a configuration may be provided in which a picture is divided into, for example, tiles in accordance with, for example, the meaning of an object in the picture. In this case, decoder 200 may decode only a partial region in a picture by selecting a tile to be decoded.);
and decode a second encoded region of the plurality of encoded regions using a second set of decoding parameters (Fig. 2, Paragraph [0210] - DRUGEON discloses a picture may include a picture header and at least one slice. A picture header includes a coding parameter which decoder 200 refers to in order to decode the at least one slice. Paragraph [0227] - DRUGEON discloses a configuration may be provided in which a picture is divided into, for example, tiles in accordance with, for example, the meaning of an object in the picture. In this case, decoder 200 may decode only a partial region in a picture by selecting a tile to be decoded.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date the claimed invention was made to combine the teachings of WANG of having a system, comprising: one or more processors to: extract at least a plurality of encoded regions from a media package; generate a plurality of regions of an image by decoding the plurality of encoded regions; and generate the image using at least the plurality of regions, with the teachings of DRUGEON of having decode a first encoded region of the plurality of encoded regions using a first set of decoding parameters; and decode a second encoded region of the plurality of encoded regions using a second set of decoding parameters.
Wherein WANG’s system wherein having decode a first encoded region of the plurality of encoded regions using a first set of decoding parameters; and decode a second encoded region of the plurality of encoded regions using a second set of decoding parameters.
The motivation behind this modification would have been to provide an enhanced system for media processing that improves coding efficiency and allows for various metadata formats, since both WANG and DRUGEON relate to methods and systems for processing media content, wherein WANG relates to storage and transport of encoded video data; infrequently changing information need not to be repeated for each sequence or picture, hence coding efficiency may be improved, and DRUGEON relates to video coding and decoding systems, components, and methods wherein an improvement in coding efficiency, an improvement in image quality, a reduction in the processing amount, and an improvement in processing efficiency can be achieved. Please see WANG (US 20190020880 A1), Paragraph [0082, 0089], and DRUGEON (US 20260197505 A1), Paragraph [0749].
Regarding claim 16, WANG in view of DRUGEON teach the system of claim 15,
WANG fails to explicitly teach wherein one or more of the first set of decoding parameters and the second set of decoding parameters are stored in the metadata.
However, DRUGEON explicitly teaches wherein one or more of the first set of decoding parameters and the second set of decoding parameters are stored in the metadata (Fig. 2, Paragraph [0226] - DRUGEON discloses decoder 200 may generate a video whose image quality has been enhanced by performing super-resolution imaging on a picture in the base layer based on the metadata. Metadata may include information for identifying a linear or a non-linear filter coefficient, as used in a super-resolution process, or information identifying a parameter value in a filter process, machine learning, or a least squares method used in super-resolution processing.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date the claimed invention was made to combine the teachings of WANG of having a system, comprising: one or more processors to: extract at least a plurality of encoded regions from a media package; generate a plurality of regions of an image by decoding the plurality of encoded regions; and generate the image using at least the plurality of regions, with the teachings of DRUGEON of having wherein one or more of the first set of decoding parameters and the second set of decoding parameters are stored in the metadata.
Wherein WANG’s system wherein one or more of the first set of decoding parameters and the second set of decoding parameters are stored in the metadata.
The motivation behind this modification would have been to provide an enhanced system for media processing that improves coding efficiency and allows for various metadata formats, since both WANG and DRUGEON relate to methods and systems for processing media content, wherein WANG relates to storage and transport of encoded video data; infrequently changing information need not to be repeated for each sequence or picture, hence coding efficiency may be improved, and DRUGEON relates to video coding and decoding systems, components, and methods wherein an improvement in coding efficiency, an improvement in image quality, a reduction in the processing amount, and an improvement in processing efficiency can be achieved. Please see WANG (US 20190020880 A1), Paragraph [0082, 0089], and DRUGEON (US 20260197505 A1), Paragraph [0749].
Examiner Remarks
In claims 9 and 17, examiner did not interpret the claims under 112(f) due to the claim language explicitly stating: “wherein the one or more processors are comprised in at least one of…”; therefore, the office understands the function of each subsequent system listed as being carried out by the processor.
Conclusion
Listed below are the prior arts made of record and not relied upon but are considered pertinent to applicant’s disclosure.
LEE et al. (US 20250234018 A1) - In the present disclosure, a method and a device for region of interest-based image encoding/decoding for machine vision may include extracting region of interest information in an image, performing an object tracking between frames based on the region of interest information, varying a resolution for each region of interest, and encoding an image with the region of interest information...… Fig. 1, Abstract.
HOSOI et al. (US 20260100045 A1) - An image processing device includes circuitry that recognizes and extracts an object included in a captured image, and that converts, using an artificial intelligence (AI) model, a region image including the object to generate a feature image. The circuitry generates a mask image by combining the captured image with the feature image… Fig. 1, Abstract.
LEE et al. (US 20250175672 A1) - Systems, apparatuses, and methods are described for dynamically assigning a plurality of spatial regions of a video frame, to a plurality of communication networks based on the current conditions of the networks, and for simultaneously sending the assigned spatial regions, or subregions, via the plurality of communication networks for reassembly at a rendering device. The video frame may be adaptively sent in response to the changing network conditions, efficiently utilizing all the available bandwidth resources of the communication networks....… Fig. 1, Abstract.
BARADEL et al. (US 20250265781 A1) - A method for recovering a 3D mesh of N humans in a 3D scene comprises: encoding a 2D image from an image capturing device to extract embedded features for each of a plurality of regions; detecting N humans in N respective regions among the plurality of regions; processing the embedded features in the N respective regions and the embedded features for each of the plurality of regions to predict body model and depth parameters using a decoder comprising a cross-attention module; providing the predicted body model parameters to a 3D parametric model for generating 3D meshes; and placing the generated 3D meshes at respective 3D spatial locations based on the predicted depth parameters....… Fig. 1, Abstract.
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/BEZAWIT NOLAWI SHIMELES/Examiner, Art Unit 2673
/CHINEYERE WILLS-BURNS/Supervisory Patent Examiner, Art Unit 2673
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