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 .
This office action is in response to amendment filed 02/03/2026 in which claims 1-18, 20, 101 are pending.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 02/03/2026 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Response to Arguments
Applicant’s arguments, see pages 7-9, filed 02/03/2026, with respect to the rejections of claims have been fully considered and amended claims 1, 12 are moot in view of a new grounds of rejection made in view of Waggoner et al. (US 12,088,821 B1).
Further since amended independent claims 1, 12 changes the scope of the invention, the dependent claims 6, 17 are also now taught by new grounds of rejection made in view of Waggoner et al. (US 12,088,821 B1).(as described in detail below).
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-4, 6-7, 12-15, 17-18, 101 are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (US 2024/0305788 A1) in view of Waggoner et al. (US 12,088,821 B1) and Tashtarian et al. (US 2025/0080787 A1)
Regarding claim 1, Liu discloses a method comprising: receiving an upload of a video from a device (Para[0045] & Fig. 1 teaches a content provider may operate video delivery system 106 to provide a content delivery service that allows entities to request and receive 1 content. The media content may be different types of content, such as on-demand videos from a library of videos and live videos); identifying a plurality of portions of the video (FIG. 2 shows an example of portions of a video); for each respective portion of the plurality of portions: accessing a quality score that is based on an analysis of visual characteristics of at least one frame (Para[0114] teaches at 2206, time domain features may be based on features associated with multiple frames. Time-domain features may describe motion speed and motion complexity of the adjacent frames, therefore, if the contents in these frames move slow and predictably, the encoding bitrate could be lower and quality could be higher, and vice versa. For example, the time domain features may be based on a similarity, a motion speed, and a motion complexity of adjacent frames); based on the respective quality score, generating a respective adaptive bitrate (ABR) ladder, by: (para[0002] teaches Adaptive Bitrate Streaming (ABR). Adaptive bitrate streaming is predicated on providing multiple streams (often referred to as variants or profiles) that are encoded at different levels of video attributes, such as different levels of bitrate and/or quality. Para[0047] teaches a video may be encoded in a profile ladder that includes multiple profiles. Each profile may correspond to different configurations, which may be different levels of bitrates and/or quality) selecting a respective set of bitrates for the respective portion (Para[0050] teaches a pre-analysis optimization process 110 may dynamically generate a list of candidate average bitrates for portions of a video. In some embodiments, pre-analysis optimization process 110 may predict respective characteristics of a portion of video, such as a rate distortion curve. Then, pre-analysis optimization process 110 selects candidate average bitrates for the portion based on analyzing the respective characteristics of the portion of video. Para[0040] optimization process 110 may dynamically select a list of candidate average bitrates for portions of a video) ; and encoding the respective portion into a respective plurality of encoded portions, wherein each encoded portion of the respective plurality of encoded portions is encoded at a bitrate of the respective set of bitrates (Para[0049] & Fig. 1 teaches segment quality driven adaptive processing system (SQA system) 108 may encode segments using a list of candidate average bitrates. Then, SQA system 108 selects segments for each profile using an optimization process. For example, SQA system 108 may adaptively select a segment with an optimal bitrate for each profile of the profile ladder while maintaining similar quality levels. SQA system 108 allows the system to maintain similar or matching quality to the target bitrate while minimizing the number of bits required to store or deliver the content & Para[0041] & Figs. 1-2 teaches SQA system 108 may process each segment of video 200 to generate multiple encodings of each respective segment based on a list of candidate average bitrates. For discussion purposes, optimization process 110 selects a list of candidate average bitrates per chunk; however, the list of candidate average bitrates may be selected for different portion sizes, such as per segment, for multiple chunks, etc.); and making the video available for streaming to a plurality of devices using each respective ABR ladder for each portion of the plurality of portions (Para[0080] & Fig. 12 teaches After encoding each segment using the list of candidate average bitrates, a selection system 1208 selects an encoded segment for each profile in a profile ladder using a selection process as described above. Selection system 1208 outputs encoded segments that are selected for the profiles in the profile ladder. para[0149] & Fig. 31 teaches the video content server 3102 may serve the video segments as directed by a user interface controller communicating with a client device. A video segment refers to a definite portion of frame-based video data, such as may be used in a streaming video session to view a television episode, motion picture, recorded live performance, or other video content).
Liu does not explicitly disclose identifying a plurality of time portions of the video; determining that the plurality of time portions of the video are stitched together from at least two respective source videos having different respective source resolutions for each respective time portion of the plurality of time portions: determining a source resolution of the respective source video that was stitched together; accessing a quality score of at least one frame of the respective time portion; determining a source resolution of the respective source video that was stitched together; based on the respective quality score and the source resolution of the respective source video, generating a respective adaptive bitrate (ABR) ladder; selecting a respective set of bitrates for the respective time portion; and encoding the respective time portion into a respective plurality of encoded portions; and making the video available for streaming to a plurality of devices using each respective ABR ladder for each time portion of the plurality of time portions.
However Waggoner discloses identifying a plurality of time portions of the video (fig. 2 & col 5 lines 23-35 input video file 106 (e.g., a portion thereof) has been encoded into encoded data 206 (e.g., a compressed version of the corresponding data of video file 106). Encoded data 206 includes a plurality of fragments (e.g., fragments 1-6) and a plurality of segments (e.g., segment 1 formed from fragments 1-3 and segment 2 formed from fragments 4-6, A fragment may have a time duration (e.g., selected from about 2 seconds to about 5 seconds in duration). A fragment may have a smaller time duration than a segment duration. A fragment time duration may be the same for the entire encoded data 206 version of input video file 106); determining that the plurality of time portions of the video are stitched together from at least two respective source videos having different respective source resolutions; (Abstract teaches determining a first resolution for a first fragment of a video file based on a first encoding complexity of the first fragment at a bitrate, encoding the first fragment at the first resolution for the bitrate to generate an encoded first fragment, determining a second different resolution for a second fragment of the video file based on a second different encoding complexity of the second fragment at the bitrate, encoding the second fragment at the second different resolution for the bitrate to generate an encoded second fragment, FIG. 4 is a flow diagram illustrating operations of a method for servicing a manifest request from a client device for a single video representation having fragments with multiple, different resolutions); for each respective time portion of the plurality of time portions: determining a source resolution of the respective source video that was stitched together ( col 6 lines 32-35 teaches scaling service 110 analyzes the fragments created from input video file 106 to determine a complexity (e.g., an encoding complexity) of the fragments (e.g., frames thereof), for example, and that complexity utilized to select a resolution from a plurality of candidate resolutions for each fragment); based on the respective quality score and the source resolution of the respective source video, generating a respective adaptive bitrate (ABR) ladder (col 6 lines 20-25 teaches scaling service 110 is to receive, as an input, the encoded data 206 of input video file 106, determine a resolution for each fragment of encoded data 206, and cause encoder 108 to encode each fragment at its determined resolution to generate a corresponding video representation 112 (e.g., the file(s) that are to be downloaded/streamed by a client device for playback of video approximating the input video file 106. In certain embodiments, the scaling service determines a resolution for each fragment that will allow that fragment to be transmitted according to a target bitrate 202. This process may be repeated for a plurality of target bitrates, col 6 lines 20-30 teaches the scaling service determines a resolution for each fragment that will allow that fragment to be transmitted according to a target bitrate 202. This process may be repeated for a plurality of target bitrates. fig. 5 & Col 10 lines 5-15 teaches operations 500 include, at block 502, determining a first resolution for a first proper subset of frames of a video file based on a first complexity of the first proper subset of frames at a bitrate. The operations 500 include, at block 504, encoding the first proper subset of frames at the first resolution for the bitrate to generate an encoded first proper subset of frames. The operations 500 include, at block 506, determining a second different resolution for a second proper subset of frames of the video file based on a second different complexity of the second proper subset of frames at the bitrate.). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to use the method that enables predicting quality values in a lower bitrate range and using an indirect mode to predict quality values in a higher bitrate range due to different prediction modes include different features in different bitrate ranges of Liu with the method of manifest for the client device is generated for identifying single video representation for the bitrate that comprises encoded first fragment with first resolution and encoded second fragment with second different resolution of Waggoner in order to provide a enables reducing resolution for bitrate when facing with complexity to allow encoding compute per pixel to improve quality at the bitrate.
Liu in view of Waggoner does not explicitly disclose accessing a quality score of at least one frame of the respective time portion; selecting a respective set of bitrates for the respective time portion; and encoding the respective time portion into a respective plurality of encoded portions; and making the video available for streaming to a plurality of devices using each respective ABR ladder for each time portion of the plurality of time portions. However Tashtarian discloses accessing a quality score of at least one frame of the respective time portion (para[0026]- [0027 teaches the origin agent may measure a quality of a plurality of produced segments by a live encoder and inform the analytics server accordingly. In this example, during the CR interval, the origin agent sends quality measures (e.g., PSNR, VMAF, and the like) of recently encoded video segments to the analytics server. The analytics server may use this information for updating the bitrate ladder. Moreover, the origin agent receives the recommended bitrate ladder from the analytics server and dictates it to a live encoder for encoding following live content (e.g., a next segment or plurality of segments. Analytics server collects quality measures of previously encoded segments in current and past timeslots. Para[0040] teaches qualities of encoded segments from origin agent 207. Analytics server 203a may implement a timeslot and run an optimization model ); selecting a respective set of bitrates for the respective time portion (Abstract During a second interval in the timeslot, an optimized bitrate ladder comprising an optimal set of bitrates (OSB) is selected using an optimization function, the optimization function taking as input quality measures and a coefficient value determined using stall information. The optimized bitrate ladder is sent to the origin server for live encoding follow-on segments & Para[0027] teaches for example, by setting α=1, the analytics server may select a subset of bitrates from set B that minimizes the average quality degradation, thereby serving clients using the client-requested bitrates & Fig. 5 & Para[0043]); and encoding the respective time portion into a respective plurality of encoded portions (Abstract teaches the optimized bitrate ladder is sent to the origin server for live encoding follow-on segments. Para[0025] teaches origin server may comprise a commodity server that hosts a live encoder program to encode received content for a live camera into different bitrates-resolutions. The segments may be delivered into a distributed network (e.g., CDN). Para[0038] & Fig. 1 teaches origin server 106 may use the updated bitrate ladder for encoding follow-on (i.e., next) segment(s) in the live content, thereby generating encoded segments 108. Origin server 106 may send encoded segments 108 to CDN servers 103a-103b); and making the video available for streaming to a plurality of devices using each respective ABR ladder for each time portion of the plurality of time portions (para[0038] teaches system 100 may comprise clients 102a-102b. Para[0042] –[0043] & Fig. 3-5 teaches Analytics server 304 may send an optimized bitrate ladder comprising an OSB to origin agent 308 for use in live encoding following (i.e., next) segment(s) in a live streaming session). During the first interval, at step 504, a frequency of requests for each bitrate in a bitrate ladder in the timeslot and a duration of a recent stall event for the client's player may be extracted from the CDN log. During a second interval in the timeslot, an optimized bitrate ladder comprising an optimal subset of bitrates (OSB) may be selected using an optimization function at step 506. The optimization function may take as input the quality measure and a coefficient value (e.g., α) determined using the frequency of requests and the duration of the recent stall event. The optimized bitrate ladder may be sent to the origin server for live encoding a next segment at step 508. In some examples, the origin agent may comprise a live encoder plugin configured to estimate a perceptual quality of every produced segment. In some examples, the origin agent also may request an encoder to adjust the bitrate ladder for live encoding further segments in accordance with the output (e.g., a decision) from the analytics server, which may include a new optimized bitrate ladder (e.g., comprising a new OSB) or an instruction to continue encoding using a previous bitrate ladder (e.g., comprising a previously selected OSB)). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to use the method that enables predicting quality values in a lower bitrate range and using an indirect mode to predict quality values in a higher bitrate range due to different prediction modes include different features in different bitrate ranges of Liu with the method enables optimizing the bitrate ladder by dynamically adjusting the number and values of bitrates and resolutions during the live session of Tashtarian in order to provide a system in which improve quality of experience (QoE) while minimizing resource consumption remains a challenging problem.
Regarding claim 2, Liu discloses the method of claim 1 wherein the quality score comprises one or more of a picture quality of the content item, assessing an amount of blur, or assessing an amount of macroblocking (Para[0047] teaches each level may be associated with another characteristic, such as a quality characteristic (e.g., resolution) para[0109] teaches adaptive quality ladder of different profiles (e.g., bitrates and resolutions), a system could predict rate distortion curves for different resolutions and bitrates. Then, the system may select different resolution and bitrate groups based on the rate distortion curves to optimize the bitrates and resolutions in the groups to set adaptive profile ladder for different videos. Para[0124] –[0127] teaches RD prediction system 1202 predicts a quality value of the current target resolution and current bitrate using the model of prediction network 2106. The prediction may receive the features for a segment and the target configuration, and output a quality value for the bitrate. For example, the prediction may be a quality value for a target resolution of 640×360 and a target bitrate 500 kbps. Para[0125] At 2410, RD prediction system 1202 moves to the next target bitrate for the resolution. The prediction may predict quality values for each resolution and bitrate pair. FIG. 25 depicts a graph 2500 that lists quality values for bitrates for one target resolution. Para[0142] teaches generation of the target quality values for multiple resolutions and bitrates).
Regarding claim 3, Liu discloses the method of claim 1 wherein the accessing the quality score comprises at least one of (a) calculating the quality score or (b) receiving a calculated quality score (para[0058] teaches FIG. 4 depicts an example of clustering encoded segments into multiple pools according to some embodiments. At 402, multiple encoded segments are shown for the candidate average bitrates. Each segment may have an associated value for a quality metric. Para[0110] teaches a prediction network 2106 may receive the segment level features and a target configuration. The target configuration may include a combination of different parameters. For example, parameters of the target configuration may include a target start frame/end frame, target resolutions, target bitrates, target quality metrics, and target encoders).
Regarding claim 4, Liu discloses the method of claim 1, wherein the respective time portion comprises a first time portion, wherein selecting the respective set of bitrates for the first time portion comprises: determining a first plurality of available bitrates (Para[0050] & Figs. 1-3 teaches pre-analysis optimization process 110 may dynamically generate a list of candidate average bitrates for portions of a video); determining that the respective quality score of the first time portion corresponds to first bitrate (Para[0053] & Figs. 1-3 teaches n the segment quality driven adaptive process, SQA system 108 may process each segment of video 200 to generate multiple encodings of each respective segment based on a list of candidate average bitrates); and selecting a first set of bitrates of the plurality of bitrates which are equal to or below the value of the first bitrate (Para[0044] & Figs. 1 -3 teaches system 100 for dynamically selecting a list of candidate average bitrates. Para[0052]-[0055] teaches the optimization process 110 may dynamically select a list of candidate average bitrates for portions of a video. At 302, optimization system 110 has selected a list of candidate average bitrates for each chunk based on characteristics of each respective chunk. For example, for chunk_0, a list of candidate average bitrates #0 is based on the characteristics for chunk_0. Also, a list of candidate average bitrates #1 is based on the characteristics for chunk_1, and so on. The candidate average bitrates may have statically included the same bitrates. A first type may be a target average bitrate and a second type may be an intermediate average bitrate. The target average bitrate may be a basic bitrate that is associated with profiles in a profile ladder for adaptive bitrate encoding. An intermediate average bitrate may be a supplement to the target average bitrate. Para[0109] & Fig. 21 teaches the system could determine a dynamic target bitrate for a higher quality with same bitrate or lower bitrate with same quality).
Regarding claim 6, Waggoner discloses the method of claim 1 wherein the analysis of visual characteristics of at least one frame of the respective time portion comprises determining a resolution of the video based on a color of a plurality of pixels in the at least one frame ( col 7 30 -38 teaches the scaling of input frame(s) of a fragment to a resolution determined for that fragment for video representation 112 includes combining a proper subset of pixels of an input frame into single pixel, e.g., combining the luminance (Y) component, blue projection chrominance (U) component, and projection chrominance (V) component for each pixel into a single, respective luminance (Y) component, blue projection chrominance (U) component, and projection chrominance (V) component.). Motivation to combine as indicated in claim 1.
Regarding claim 7, Tashtarian discloses the method of claim 1, wherein making the video available for streaming to the plurality of devices comprises updating a manifest to reflect each respective ABR ladder for each time portion of the plurality of time portions (Para[0026]–[0027] teaches the optimizing a bitrate ladder may operate in a timeslot manner. Analytics server may use this information for updating the bitrate ladder. Moreover, the origin agent receives the recommended bitrate ladder from the analytics server and dictates it to a live encoder for encoding following live content (e.g., a next segment or plurality of segments). Any modifications made to the bitrate ladder are invisible to clients (e.g., players). A client receives a manifest, denoted by custom character, that includes m different bitrates-resolutions (i.e., representations), which remain constant throughout a streaming session. A client may choose a representation from the manifest and send an HTTP request to buffer a subsequent segment. If the segment with the requested bitrate is present on the CDN server, the client may obtain it. Otherwise, the CDN server responds to the request by providing a segment encoded at a lower bitrate. In each OL interval, the analytics server may select an optimal subset of m bitrates (i.e., OSB), which may then be communicated to the origin agent. The live encoder may use the updated OSB to encode the live content). Motivation to combine as indicated in claim 1.
Regarding claim 12, Liu discloses a system comprising input/output circuitry configured to receive an upload of a video from a device (Para[0045] & Fig. 1 teaches a content provider may operate video delivery system 106 to provide a content delivery service that allows entities to request and receive 1 content. The media content may be different types of content, such as on-demand videos from a library of videos and live videos); control circuitry configured to: identify a plurality of portions of the video (FIG. 2 shows an example of portions of a video); for each respective portion of the plurality of portions: access a quality score that is based on an analysis of visual characteristics of at least one frame of the respective portion (Para[0114] teaches at 2206, time domain features may be based on features associated with multiple frames. Time-domain features may describe motion speed and motion complexity of the adjacent frames, therefore, if the contents in these frames move slow and predictably, the encoding bitrate could be lower and quality could be higher, and vice versa. For example, the time domain features may be based on a similarity, a motion speed, and a motion complexity of adjacent frames); based on the respective quality score, generate a respective adaptive bitrate (ABR) ladder by (para[0002] teaches Adaptive Bitrate Streaming (ABR). Adaptive bitrate streaming is predicated on providing multiple streams (often referred to as variants or profiles) that are encoded at different levels of video attributes, such as different levels of bitrate and/or quality. Para[0047] teaches a video may be encoded in a profile ladder that includes multiple profiles. Each profile may correspond to different configurations, which may be different levels of bitrates and/or quality):select a respective set of bitrates for the respective portion (Para[0050] teaches a pre-analysis optimization process 110 may dynamically generate a list of candidate average bitrates for portions of a video. In some embodiments, pre-analysis optimization process 110 may predict respective characteristics of a portion of video, such as a rate distortion curve. Then, pre-analysis optimization process 110 selects candidate average bitrates for the portion based on analyzing the respective characteristics of the portion of video. Para[0040] optimization process 110 may dynamically select a list of candidate average bitrates for portions of a video); and encode the respective portion into a respective plurality of encoded portions, wherein each encoded portion of the respective plurality of encoded portions is encoded at a bitrate of the respective set of bitrates (Para[0049] & Fig. 1 teaches segment quality driven adaptive processing system (SQA system) 108 may encode segments using a list of candidate average bitrates. Then, SQA system 108 selects segments for each profile using an optimization process. For example, SQA system 108 may adaptively select a segment with an optimal bitrate for each profile of the profile ladder while maintaining similar quality levels. SQA system 108 allows the system to maintain similar or matching quality to the target bitrate while minimizing the number of bits required to store or deliver the content & Para[0041] & Figs. 1-2 teaches SQA system 108 may process each segment of video 200 to generate multiple encodings of each respective segment based on a list of candidate average bitrates. For discussion purposes, optimization process 110 selects a list of candidate average bitrates per chunk; however, the list of candidate average bitrates may be selected for different portion sizes, such as per segment, for multiple chunks, etc.); and make the video available for streaming to a plurality of devices using each respective ABR ladder for each portion of the plurality of portions. (Para[0080] & Fig. 12 teaches After encoding each segment using the list of candidate average bitrates, a selection system 1208 selects an encoded segment for each profile in a profile ladder using a selection process as described above. Selection system 1208 outputs encoded segments that are selected for the profiles in the profile ladder. para[0149] & Fig. 31 teaches the video content server 3102 may serve the video segments as directed by a user interface controller communicating with a client device. A video segment refers to a definite portion of frame-based video data, such as may be used in a streaming video session to view a television episode, motion picture, recorded live performance, or other video content).
Liu does not explicitly disclose identify a plurality of time portions of the video;
determine that the plurality of time portions of the video are stitched together from at least two respective source videos having different respective source resolutions; for each respective time portion of the plurality of time portions: determine a source resolution of the respective source video that was stitched together; access a quality score that is based on an analysis of visual characteristics of at least one frame of the respective time portion; based on the respective quality score and the source resolution of the respective source video, generate a respective adaptive bitrate (ABR) ladder by: select a respective set of bitrates for the respective time portion; and encode the respective time portion into a respective plurality of encoded portions; and make the video available for streaming to a plurality of devices using each respective ABR ladder for each time portion of the plurality of time portions.
However Waggoner discloses identify a plurality of time portions of the video (fig. 2 & col 5 lines 23-35 input video file 106 (e.g., a portion thereof) has been encoded into encoded data 206 (e.g., a compressed version of the corresponding data of video file 106). Encoded data 206 includes a plurality of fragments (e.g., fragments 1-6) and a plurality of segments (e.g., segment 1 formed from fragments 1-3 and segment 2 formed from fragments 4-6, A fragment may have a time duration (e.g., selected from about 2 seconds to about 5 seconds in duration). A fragment may have a smaller time duration than a segment duration. A fragment time duration may be the same for the entire encoded data 206 version of input video file 106); determine that the plurality of time portions of the video are stitched together from at least two respective source videos having different respective source resolutions; (Abstract teaches determining a first resolution for a first fragment of a video file based on a first encoding complexity of the first fragment at a bitrate, encoding the first fragment at the first resolution for the bitrate to generate an encoded first fragment, determining a second different resolution for a second fragment of the video file based on a second different encoding complexity of the second fragment at the bitrate, encoding the second fragment at the second different resolution for the bitrate to generate an encoded second fragment, FIG. 4 is a flow diagram illustrating operations of a method for servicing a manifest request from a client device for a single video representation having fragments with multiple, different resolutions); for each respective time portion of the plurality of time portions: determine a source resolution of the respective source video that was stitched together ( col 6 lines 32-35 teaches scaling service 110 analyzes the fragments created from input video file 106 to determine a complexity (e.g., an encoding complexity) of the fragments (e.g., frames thereof), for example, and that complexity utilized to select a resolution from a plurality of candidate resolutions for each fragment); based on the respective quality score and the source resolution of the respective source video, generating a respective adaptive bitrate (ABR) ladder (col 6 lines 20-25 teaches scaling service 110 is to receive, as an input, the encoded data 206 of input video file 106, determine a resolution for each fragment of encoded data 206, and cause encoder 108 to encode each fragment at its determined resolution to generate a corresponding video representation 112 (e.g., the file(s) that are to be downloaded/streamed by a client device for playback of video approximating the input video file 106. In certain embodiments, the scaling service determines a resolution for each fragment that will allow that fragment to be transmitted according to a target bitrate 202. This process may be repeated for a plurality of target bitrates, col 6 lines 20-30 teaches the scaling service determines a resolution for each fragment that will allow that fragment to be transmitted according to a target bitrate 202. This process may be repeated for a plurality of target bitrates. fig. 5 & Col 10 lines 5-15 teaches operations 500 include, at block 502, determining a first resolution for a first proper subset of frames of a video file based on a first complexity of the first proper subset of frames at a bitrate. The operations 500 include, at block 504, encoding the first proper subset of frames at the first resolution for the bitrate to generate an encoded first proper subset of frames. The operations 500 include, at block 506, determining a second different resolution for a second proper subset of frames of the video file based on a second different complexity of the second proper subset of frames at the bitrate.). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to use the method that enables predicting quality values in a lower bitrate range and using an indirect mode to predict quality values in a higher bitrate range due to different prediction modes include different features in different bitrate ranges of Liu with the method of manifest for the client device is generated for identifying single video representation for the bitrate that comprises encoded first fragment with first resolution and encoded second fragment with second different resolution of Waggoner in order to provide a enables reducing resolution for bitrate when facing with complexity to allow encoding compute per pixel to improve quality at the bitrate.
Liu in view of Waggoner discloses access a quality score that is based on an analysis of visual characteristics of at least one frame of the respective time portion; based on the respective quality score, generate a respective adaptive bitrate (ABR) ladder by: select a respective set of bitrates for the respective time portion; and encode the respective time portion into a respective plurality of encoded portions; and make the video available for streaming to a plurality of devices using each respective ABR ladder for each time portion of the plurality of time portions. However Tashtarian access a quality score of at least one frame of the respective time portion (para[0026]- [0027 teaches the origin agent may measure a quality of a plurality of produced segments by a live encoder and inform the analytics server accordingly. In this example, during the CR interval, the origin agent sends quality measures (e.g., PSNR, VMAF, and the like) of recently encoded video segments to the analytics server. The analytics server may use this information for updating the bitrate ladder. Moreover, the origin agent receives the recommended bitrate ladder from the analytics server and dictates it to a live encoder for encoding following live content (e.g., a next segment or plurality of segments. Analytics server collects quality measures of previously encoded segments in current and past timeslots. Para[0040] teaches qualities of encoded segments from origin agent 207. Analytics server 203a may implement a timeslot and run an optimization model ); select a respective set of bitrates for the respective time portion (Abstract During a second interval in the timeslot, an optimized bitrate ladder comprising an optimal set of bitrates (OSB) is selected using an optimization function, the optimization function taking as input quality measures and a coefficient value determined using stall information. The optimized bitrate ladder is sent to the origin server for live encoding follow-on segments & Para[0027] teaches for example, by setting α=1, the analytics server may select a subset of bitrates from set B that minimizes the average quality degradation, thereby serving clients using the client-requested bitrates & Fig. 5 & Para[0043]); and encode the respective time portion into a respective plurality of encoded portions (Abstract teaches the optimized bitrate ladder is sent to the origin server for live encoding follow-on segments. Para[0025] teaches origin server may comprise a commodity server that hosts a live encoder program to encode received content for a live camera into different bitrates-resolutions. The segments may be delivered into a distributed network (e.g., CDN). Para[0038] & Fig. 1 teaches origin server 106 may use the updated bitrate ladder for encoding follow-on (i.e., next) segment(s) in the live content, thereby generating encoded segments 108. Origin server 106 may send encoded segments 108 to CDN servers 103a-103b); and make the video available for streaming to a plurality of devices using each respective ABR ladder for each time portion of the plurality of time portions (para[0038] teaches system 100 may comprise clients 102a-102b. Para[0042] –[0043] & Fig. 3-5 teaches Analytics server 304 may send an optimized bitrate ladder comprising an OSB to origin agent 308 for use in live encoding following (i.e., next) segment(s) in a live streaming session). During the first interval, at step 504, a frequency of requests for each bitrate in a bitrate ladder in the timeslot and a duration of a recent stall event for the client's player may be extracted from the CDN log. During a second interval in the timeslot, an optimized bitrate ladder comprising an optimal subset of bitrates (OSB) may be selected using an optimization function at step 506. The optimization function may take as input the quality measure and a coefficient value (e.g., α) determined using the frequency of requests and the duration of the recent stall event. The optimized bitrate ladder may be sent to the origin server for live encoding a next segment at step 508. In some examples, the origin agent may comprise a live encoder plugin configured to estimate a perceptual quality of every produced segment. In some examples, the origin agent also may request an encoder to adjust the bitrate ladder for live encoding further segments in accordance with the output (e.g., a decision) from the analytics server, which may include a new optimized bitrate ladder (e.g., comprising a new OSB) or an instruction to continue encoding using a previous bitrate ladder (e.g., comprising a previously selected OSB)). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to use the method that enables predicting quality values in a lower bitrate range and using an indirect mode to predict quality values in a higher bitrate range due to different prediction modes include different features in different bitrate ranges of Liu with the method enables optimizing the bitrate ladder by dynamically adjusting the number and values of bitrates and resolutions during the live session of Tashtarian in order to provide a system in which improve quality of experience (QoE) while minimizing resource consumption remains a challenging problem.
Regarding claim 13, Liu discloses the system of claim 12 wherein the quality score comprises one or more of a picture quality of the content item, assessing an amount of blur, or assessing an amount of macroblocking (Para[0047] teaches each level may be associated with another characteristic, such as a quality characteristic (e.g., resolution) para[019] teaches adaptive quality ladder of different profiles (e.g., bitrates and resolutions), a system could predict rate distortion curves for different resolutions and bitrates. Then, the system may select different resolution and bitrate groups based on the rate distortion curves to optimize the bitrates and resolutions in the groups to set adaptive profile ladder for different videos. Para[0124] –[0127] teaches RD prediction system 1202 predicts a quality value of the current target resolution and current bitrate using the model of prediction network 2106. The prediction may receive the features for a segment and the target configuration, and output a quality value for the bitrate. For example, the prediction may be a quality value for a target resolution of 640×360 and a target bitrate 500 kbps. [0125] At 2410, RD prediction system 1202 moves to the next target bitrate for the resolution. The prediction may predict quality values for each resolution and bitrate pair. FIG. 25 depicts a graph 2500 that lists quality values for bitrates for one target resolution. Para[0142] teaches generation of the target quality values for multiple resolutions and bitrates).
Regarding claim 14, Liu discloses the system of claim 12 wherein the control circuitry is configured to access the quality score by at least one of (a) calculating the quality score or (b) receiving a calculated quality score (para[0058] teaches FIG. 4 depicts an example of clustering encoded segments into multiple pools according to some embodiments. At 402, multiple encoded segments are shown for the candidate average bitrates. Each segment may have an associated value for a quality metric. Para[0110] teaches a prediction network 2106 may receive the segment level features and a target configuration. The target configuration may include a combination of different parameters. For example, parameters of the target configuration may include a target start frame/end frame, target resolutions, target bitrates, target quality metrics, and target encoders).
Regarding claim 15, Liu discloses the system of claim 12, wherein the respective time portion comprises a first time portion, wherein the control circuitry is configured to select the respective set of bitrates for the first time portion by: determining a first plurality of available bitrates (Para[0050] & Figs. 1-3 teaches pre-analysis optimization process 110 may dynamically generate a list of candidate average bitrates for portions of a video); determining that the respective quality score of the first time portion corresponds to first bitrate (Para[0053] & Figs. 1-3 teaches n the segment quality driven adaptive process, SQA system 108 may process each segment of video 200 to generate multiple encodings of each respective segment based on a list of candidate average bitrates); and selecting a first set of bitrates of the plurality of bitrates which are equal to or below the value of the first bitrate (Para[0044] & Figs. 1 -3 teaches system 100 for dynamically selecting a list of candidate average bitrates. Para[0052]-[0055] teaches the optimization process 110 may dynamically select a list of candidate average bitrates for portions of a video. At 302, optimization system 110 has selected a list of candidate average bitrates for each chunk based on characteristics of each respective chunk. For example, for chunk_0, a list of candidate average bitrates #0 is based on the characteristics for chunk_0. Also, a list of candidate average bitrates #1 is based on the characteristics for chunk_1, and so on. The candidate average bitrates may have statically included the same bitrates. A first type may be a target average bitrate and a second type may be an intermediate average bitrate. The target average bitrate may be a basic bitrate that is associated with profiles in a profile ladder for adaptive bitrate encoding. An intermediate average bitrate may be a supplement to the target average bitrate. Para[0109] & Fig. 21 teaches the system could determine a dynamic target bitrate for a higher quality with same bitrate or lower bitrate with same quality).
Regarding claim 17, Waggoner discloses the system of claim 12 wherein the control circuitry is configured to analyze of visual characteristics of at least one frame of the respective time portion by determining a resolution of the video based on a color of a plurality of pixels in the at least one frame (col 7 30 -38 teaches the scaling of input frame(s) of a fragment to a resolution determined for that fragment for video representation 112 includes combining a proper subset of pixels of an input frame into single pixel, e.g., combining the luminance (Y) component, blue projection chrominance (U) component, and projection chrominance (V) component for each pixel into a single, respective luminance (Y) component, blue projection chrominance (U) component, and projection chrominance (V) component.). Motivation to combine as indicated in claim 1.
Regarding claim 18, Tashtarian discloses the system of claim 12, wherein the control circuitry is configured to make the video available for streaming to the plurality of devices by updating a manifest to reflect each respective ABR ladder for each time portion of the plurality of time portions (Para[0026]–[0027] teaches the analytics server may use this information for updating the bitrate ladder. Moreover, the origin agent receives the recommended bitrate ladder from the analytics server and dictates it to a live encoder for encoding following live content (e.g., a next segment or plurality of segments). Any modifications made to the bitrate ladder are invisible to clients (e.g., players). A client receives a manifest, denoted by custom character, that includes m different bitrates-resolutions (i.e., representations), which remain constant throughout a streaming session. A client may choose a representation from the manifest and send an HTTP request to buffer a subsequent segment. If the segment with the requested bitrate is present on the CDN server, the client may obtain it. Otherwise, the CDN server responds to the request by providing a segment encoded at a lower bitrate. In each OL interval, the analytics server may select an optimal subset of m bitrates (i.e., OSB), which may then be communicated to the origin agent. The live encoder may use the updated OSB to encode the live content). Motivation to combine as indicated in claim 12.
Regarding claim 101, Waggoner discloses the method of claim 1, further comprising: determining that enhancement for at least one of the plurality of time portions is needed; and applying enhancements to the at least one of the plurality of time portions, wherein the respective adaptive bitrate (ABR) ladder is generated based at least partly on the enhanced at least one of the plurality of time portions (col 8 lines 25-35 teaches scaling service 110 may select the resolutions based on (e.g., target bitrate 202 and) such that the resulting fragment resolutions increase the encoder speed, for example, to redistribute encoding compute resources to certain frame(s)/fragments(s) when the content is challenging and/or to balance total output of the encode (e.g., in pixels/second) across streams). Motivation to combine as indicated in claim 1.
Claims 5, 16 are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (US 2024/0305788 A1) in view of Waggoner et al. (US 12,088,821 B1) and Tashtarian et al. (US 2025/0080787 A1) in further view of Liu et al. (US 2024/0305842 A1) (hereinafter Liu II).
Regarding claim 5, Liu in view of Waggoner and Tashtarian discloses the method of claim 4, Liu in view of Waggoner and Tashtarian does not explicitly disclose wherein the respective time portion comprises a second time portion; wherein selecting the respective set of bitrates for the respective time portion comprises: determining a second plurality of available bitrates; determining that the respective quality score of the second time portion corresponds to a second bitrate not equal to the first bitrate; and selecting a second set of bitrates different than the first set of bitrates of the plurality of bitrates which are equal to or below the value of the second bitrate. However Liu II discloses wherein the respective time portion comprises a second time portion (Abstract teaches second representation is analyzed to determine a second list of bitrates for the second portion of video), wherein selecting the respective set of bitrates for the respective time portion comprises: determining a second plurality of available bitrates (Para[0027] teaches system may dynamically select a list of candidate average bitrates for different portions of the video, such as for different chunks of the video, the list of candidate average bitrates may be set for different portions of the video. para[0041] teaches The bitrates included in each respective list of candidate average bitrates may be optimized based on characteristics associated with the respective portion of video that will use the list of candidate average bitrates (e.g., a chunk and/or segments). Given different characteristics for different chunks, respective lists of candidate average bitrates may be different); determining that the respective quality score of the second time portion corresponds to a second bitrate not equal to the first bitrate (para[0056] & Fig. 8 teaches relationship between quality and bitrate for video content. The different rate distortion curves may be illustrated for different chunks of a video; however, the rate distortion curves may be different for different portions of a video, such as segments, chunks, multiple chunks, or different videos. Para[0059] & FIG. 10 depicts an example of using static candidate average bitrates for different rate distortion curves .Graphs 802, 804 and 806 depict the different rate distortion curves for different chunks that were shown in FIG. 8. The dotted lines in each graph show the different bitrates of the list of candidate average bitrates); and selecting a second set of bitrates different than the first set of bitrates of the plurality of bitrates which are equal to or below the value of the second bitrate (Abstract teaches the first list of bitrates is different from the second list of bitrates. Para[0041] teaches The bitrates included in each respective list of candidate average bitrates may be optimized based on characteristics associated with the respective portion of video that will use the list of candidate average bitrates (e.g., a chunk and/or segments). Given different characteristics for different chunks, respective lists of candidate average bitrates may be different & Para[0081] Fig. 16 At 1608, CAB list optimization system 1204 outputs the minimum bitrate and the maximum bitrate for the chunk. In this case, the lowest minimum bitrate from the minimum bitrates for the segments is selected and the highest maximum bitrate from the maximum bitrates for the segments is selected ). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to use the method that enables predicting quality values in a lower bitrate range and using an indirect mode to predict quality values in a higher bitrate range enables optimizing the bitrate ladder by dynamically adjusting the number and values of bitrates and resolutions of Liu in view of Waggoner and Tashtarian with the method which involves generating a first representation of a first relationship between bitrate and quality by a computing device based on first features of a first portion of a video. A second representation of a second relationship between bitrate and quality is generated by the computing device based on second features of a second portion of a video of Liu II in order to provide a system in which higher quality video and viewing experience because the segment quality-driven adaptive process realizes a better selection of encoded segments to select from to form the profiles for the profile ladder.
Regarding claim 16, Liu in view of Waggoner and Tashtarian discloses the system of claim 15, Liu in view of Tashtarian Waggoner and does not explicitly disclose, wherein the respective time portion comprises a second time portion, wherein the control circuitry is configured to select the respective set of bitrates for the respective time portion by: determining a second plurality of available bitrates; determining that the respective quality score of the second time portion corresponds to a second bitrate not equal to the first bitrate; and selecting a second set of bitrates different than the first set of bitrates of the plurality of bitrates which are equal to or below the value of the second bitrate. However Li II discloses wherein the respective time portion comprises a second time portion (Abstract teaches second representation is analyzed to determine a second list of bitrates for the second portion of video), wherein the control circuitry is configured to select the respective set of bitrates for the respective time portion by: determining a second plurality of available bitrates (Para[0027] teaches system may dynamically select a list of candidate average bitrates for different portions of the video, such as for different chunks of the video, the list of candidate average bitrates may be set for different portions of the video. para[0041] teaches The bitrates included in each respective list of candidate average bitrates may be optimized based on characteristics associated with the respective portion of video that will use the list of candidate average bitrates (e.g., a chunk and/or segments). Given different characteristics for different chunks, respective lists of candidate average bitrates may be different); determining that the respective quality score of the second time portion corresponds to a second bitrate not equal to the first bitrate (para[0056] & Fig. 8 teaches relationship between quality and bitrate for video content. The different rate distortion curves may be illustrated for different chunks of a video; however, the rate distortion curves may be different for different portions of a video, such as segments, chunks, multiple chunks, or different videos. Para[0059] & FIG. 10 depicts an example of using static candidate average bitrates for different rate distortion curves. Graphs 802, 804 and 806 depict the different rate distortion curves for different chunks that were shown in FIG. 8. The dotted lines in each graph show the different bitrates of the list of candidate average bitrates); and selecting a second set of bitrates different than the first set of bitrates of the plurality of bitrates which are equal to or below the value of the second bitrate (Abstract teaches the first list of bitrates is different from the second list of bitrates. Para[0041] teaches The bitrates included in each respective list of candidate average bitrates may be optimized based on characteristics associated with the respective portion of video that will use the list of candidate average bitrates (e.g., a chunk and/or segments). Given different characteristics for different chunks, respective lists of candidate average bitrates may be different & Para[0081] Fig. 16 At 1608, CAB list optimization system 1204 outputs the minimum bitrate and the maximum bitrate for the chunk. In this case, the lowest minimum bitrate from the minimum bitrates for the segments is selected and the highest maximum bitrate from the maximum bitrates for the segments is selected ). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to use the method that enables predicting quality values in a lower bitrate range and using an indirect mode to predict quality values in a higher bitrate range enables optimizing the bitrate ladder by dynamically adjusting the number and values of bitrates and resolutions of Liu in view of Waggoner and Tashtarian with the method which involves generating a first representation of a first relationship between bitrate and quality by a computing device based on first features of a first portion of a video. A second representation of a second relationship between bitrate and quality is generated by the computing device based on second features of a second portion of a video of Liu II in order to provide a system in which higher quality video and viewing experience because the segment quality-driven adaptive process realizes a better selection of encoded segments to select from to form the profiles for the profile ladder.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over .
Liu et al. (US 2024/0305788 A1) in view of Waggoner et al. (US 12,088,821 B1) and Tashtarian et al. (US 2025/0080787 A1) in further view of Phillips et al. (US 2017/0070551 A1).
Regarding claim 8, Liu in view of Waggoner and Tashtarian discloses the method of claim 1, Liu in view of Tashtarian Waggoner and does not explicitly disclose wherein making the video available for streaming to the plurality of devices comprises transmitting a plurality of network addresses to a user gateway, wherein each network address of the plurality of network addresses corresponds to a bitrate of the plurality of bitrates. However Phillips discloses wherein making the video available for streaming to the plurality of devices comprises transmitting a plurality of network addresses to a user gateway, wherein each network address of the plurality of network addresses corresponds to a bitrate of the plurality of bitrates (Para [0054] FIG. 4 is a block diagram of a node or element 400 operative in an example an MABR communications network. wherein an ABR video management agent or functionality 404 may be realized as a virtual function or machine on a host hardware/software platform 402, e.g., in a network agent implementation or in a premises gateway agent implementation. As described previously, a plurality of MABR gapped/segmented streams 405 comprising various bitrate representations of multicast service channels are received by node 402 at corresponding multicast IP addresses. Fig. 9 & Para[0060] teaches At block 902, a channel change (CC) request is received from a client device, e.g., an STB disposed in a subscriber premises, to change to a target service provided or otherwise available as a plurality of MABR streams, each corresponding to a particular bitrate representation of the target service channel, wherein the subscriber premises includes one or more progressive download ABR client devices that may be engaged in respective ABR sessions. At block 904, a determination may be made as to identifying, calculating, or otherwise obtaining, a select bitrate representation of the target service channel to which the requesting STB is to be joined or switched). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to use the method that enables predicting quality values in a lower bitrate range and using an indirect mode to predict quality values in a higher bitrate range enables optimizing the bitrate ladder by dynamically adjusting the number and values of bitrates and resolutions of Liu in view of Waggoner and Tashtarian with the method of adjusting progressive download ABR client devices bitrates associated with download sessions so that correct bitrate quality for a target service channel is reached if a select bitrate representation of the target service channel is not at a correct bitrate quality provisioned of Phillips in order to provide a system that enables using a recovery segment to provide necessary header information as quickly as possible at a correct bitrate to allow a bandwidth-optimized channel changing process in a multicast communications network.
Claims 9, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (US 2024/0305788 A1) in view of Waggoner et al. (US 12,088,821 B1) and Tashtarian et al. (US 2025/0080787 A1) in further view of Chen et al. (US 2024/0073462 A1).
Regarding claim 9, Liu in view of Waggoner and Tashtarian discloses the method of claim 1. Liu in view of Waggoner and Tashtarian does not explicitly disclose further comprising determining, based on the respective quality score, that the respective time portion requires enhancement . However Chen discloses further comprising determining, based on the respective quality score, that the respective time portion requires enhancement (Abstract teaches the first segment is processed to improve the quality of the first segment, and the content item is updated with the improved-quality first segment. Para[0025]-[0027] teaches a segment that is identified to be below a threshold quality level is processed 110 to improve the quality. the pre-trained neural networks may represent general purpose filters for video quality enhancement, for example, spatial upsampling to improve the resolution of the segment. [0039] teaches different priorities may be given to improving the quality of different segments of the first content item depending on the quality of those segments. For example, segments of a relatively low quality, e.g., segments with a resolution of 360p, can be targeted for higher-priority improvement than segments of a relatively high quality). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to use the method that enables predicting quality values in a lower bitrate range and using an indirect mode to predict quality values in a higher bitrate range enables optimizing the bitrate ladder by dynamically adjusting the number and values of bitrates and resolutions of Liu in view of Waggoner and Tashtarian with the method in which the segment is processed to improve the quality of the segment. The content item is updated with the improved-quality segment of Chen in order to provide a system in which allows a user to select a higher-quality segment of the content item to be processed and replaced with a high-quality corresponding segment, so that the user can experience a better quality of a live streaming experience.
Regarding claim 20, Liu in view of Waggoner and Tashtarian discloses the system of claim 12 Liu in view of Waggoner and Tashtarian does not explicitly disclose wherein the control circuitry is further configured to determine, based on the respective quality score, that the respective time portion requires enhancement. However Chen wherein the control circuitry is further configured to determine, based on the respective quality score, that the respective time portion requires enhancement (Abstract teaches the first segment is processed to improve the quality of the first segment, and the content item is updated with the improved-quality first segment. Para[0025]-[0027] teaches a segment that is identified to be below a threshold quality level is processed 110 to improve the quality. the pre-trained neural networks may represent general purpose filters for video quality enhancement, for example, spatial upsampling to improve the resolution of the segment. [0039] teaches different priorities may be given to improving the quality of different segments of the first content item depending on the quality of those segments. For example, segments of a relatively low quality, e.g., segments with a resolution of 360p, can be targeted for higher-priority improvement than segments of a relatively high quality). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to use the method that enables predicting quality values in a lower bitrate range and using an indirect mode to predict quality values in a higher bitrate range enables optimizing the bitrate ladder by dynamically adjusting the number and values of bitrates and resolutions of Liu in view of Waggoner and Tashtarian with the method in which the segment is processed to improve the quality of the segment. The content item is updated with the improved-quality segment of Chen in order to provide a system in which allows a user to select a higher-quality segment of the content item to be processed and replaced with a high-quality corresponding segment, so that the user can experience a better quality of a live streaming experience.
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable over .
Liu et al. (US 2024/0305788 A1) in view of Waggoner et al. (US 12,088,821 B1) and Tashtarian et al. (US 2025/0080787 A1) in further view of McGilvray et al. (US 2021/0409796 A1).
Regarding 10, Liu in view of Waggoner and Tashtarian discloses the method of claim 1, Liu in view of Waggoner and Tashtarian does not explicitly disclose further comprising: capturing a first video associated with a first quality score and a second video associated with a second quality score; and generating the video by editing together the first video and the second video. However McGilvray discloses further comprising: capturing a first video associated with a first quality score and a second video associated with a second quality score (Para[0076] & Fig. 3B teaches For example, the first live broadcasting stream 102 may include the multiple streaming contents such as a first streaming content using HD quality and a second streaming content using UHD quality, para[0115] teaches a live content origination source may produce and/or provide live streaming content using a high streaming quality (e.g., the second streaming format 302 and/or 306) as well as a low streaming quality (e.g., the first streaming format 300 and/or 304)); and generating the video by editing together the first video and the second video (Para[0099] teaches the station manifest file 240 and/or the NOC manifest file 242 may be received in the form of a merged manifest file associated with a hybrid stream received directly from the first content origination source 108 and/or the second content origination source 110. For example, in such embodiments, the first live broadcasting stream 102 and/or the second live broadcasting stream 104 may include a respective rules engine (e.g., similar to the rules engine 112) receiving multiple live broadcasting streams and providing the hybrid stream to the manifest switcher 162, para[0101] teaches the merged manifest file 244 may cause provision of the first live broadcasting stream 102 or the second live broadcasting stream 104 to the content viewing devices 106 via a common channel (e.g., the hybrid stream 114)). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to use the method that enables predicting quality values in a lower bitrate range and using an indirect mode to predict quality values in a higher bitrate range enables optimizing the bitrate ladder by dynamically adjusting the number and values of bitrates and resolutions of Liu in view of Waggoner and Tashtarian with the method for enabling switching between multiple broadcasting streams displayed on media viewing devices of McGilvray in order to provide a format agnostic content distribution flow to enable content distribution channels to support a wide variety of content formats
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Liu et al. (US 2024/0305788 A1) in view of Waggoner et al. (US 12,088,821 B1) and Tashtarian et al. (US 2025/0080787 A1) in further view of McGilvray et al. (US 2021/0409796 A1) and Mao et al. (US 2019/0208214 A1).
Regarding 11, Liu in view of Waggoner and Tashtarian in further view McGilvray discloses the method of claim 10, Liu in view of Waggoner and Tashtarian in further view McGilvray does not explicitly disclose further comprising: accessing metadata associated with the video indicating an overall quality score associated with the video; and determining that a quality score associated with a first time portion of the plurality of time portions does not equal the overall quality score indicated by the metadata. However Mao discloses further comprising: accessing metadata associated with the video indicating an overall quality score associated with the video (Para[0020] teaches the metadata may comprise data that suggests an overall quality level of the encoded media content item); and determining that a quality score associated with a first time portion of the plurality of time portions does not equal the overall quality score indicated by the metadata (para[0050] teaches the prediction engine 100 may analyze the received metadata in step 403. The analysis of step 403 may comprise determining whether a quality of an encoded media content item corresponding to the received metadata is optimized. This determination may comprise a determination that the quality is too low and that the media content item should be encoded again at the current resolution, but at a higher bit rate. Determining that the quality is too low may comprise determining that one or more quality-indicating parameters has a value below a predefined threshold for a particular type of content. As but on example, PSNR values of T1 or higher may correlate with a minimum acceptable quality level. If the metadata received in step 402 indicates a PSNR below T1, the prediction engine 100 may determine that the media content item corresponding to that metadata should be encoded at the same resolution but at a higher bit rate). It would have been obvious to one having ordinary skill in the art before the effective filing date of the invention to use the method that enables predicting quality values in a lower bitrate range and using an indirect mode to predict quality values in a higher bitrate range enables optimizing the bitrate ladder by dynamically adjusting the number and values of bitrates and resolutions from multiple broadcasting streams of Liu in view of Waggoner and Tashtarian in further view McGilvray with the encoders send metadata in batches for quickly-performed encoding processes, but can send metadata for every longer encoding process performed of Mao in order to provide a system to maximize computational efficiency and avoid unnecessary repetition of long encoding processes.
Conclusion
THIS ACTION IS MADE FINAL. 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.
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/ROWINA J CATTUNGAL/Primary Examiner, Art Unit 2425