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公开(公告)号：US11575947B2
公开(公告)日：2023-02-07
申请号：US17338764
申请日：2021-06-04
Applicant: Adobe Inc.
Inventor： Viswanathan Swaminathan , Saayan Mitra , Akshay Malhotra
IPC: H04N19/94 , H04N19/46 , H04N19/91 , H04N21/274 , G06T9/00
Abstract: Residual vectors are compressed in a lossless compression scheme suitable for cloud DVR video content applications. Thus, a cloud DVR service provider can take many copies of the same file stored in the cloud and save storage space by compressing those copies while still maintaining their status as distinct copies, one per user. Vector quantization is used for compressing already-compressed video streams (e.g., MPEG streams). As vector quantization is a lossy compression scheme, the residual vector has to be stored to regenerate the original video stream at the decoding (playback) node. Entropy coding schemes like Arithmetic or Huffman coding can be used to compress the residual vectors. Additional strategies can be implemented to further optimize this residual compression. In some embodiments, the techniques operate to provide a 25-50% improvement in compression. Storage space is thus more efficiently used and video transmission may be faster in some cases.
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公开(公告)号：US11348130B2
公开(公告)日：2022-05-31
申请号：US16995530
申请日：2020-08-17
Applicant: Adobe Inc.
Inventor： Chih Hsin Hsueh , Viswanathan Swaminathan , Venkata Karthik Penikalapati , Seth Olson , Michael Schiff , Gang Wu , Daniel Pang , Alok Kothari
Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods to generate sketches for clearing-bid values and bid-success rates based on multi-dimensional targeting criteria for a digital-content campaign and dynamically determine predicted values for the digital-content campaign based on the sketches. To illustrate, the disclosed systems can use a running-average-tuple-sketch to generate tuple sketches of historical clearing-bid values and tuple sketches of historical bid-success-rates from historical auction data. Based on the tuple sketches, the disclosed systems can determine one or more of a predicted cost per quantity of impressions, a predicted number of impressions, or a predicted expenditure for the digital-content campaign—according to user-input targeting criteria and expenditure constraints.
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公开(公告)号：US20210400278A1
公开(公告)日：2021-12-23
申请号：US17446862
申请日：2021-09-03
Applicant: Adobe Inc.
Inventor： Viswanathan Swaminathan , Rashmi Mittal
IPC: H04N19/13 , H04N19/94 , H04N19/176 , H04N19/196
Abstract: Techniques are disclosed for the improvement of vector quantization (VQ) codebook generation. The improved codebooks may be used for compression in cloud-based video applications. VQ achieves compression by vectorizing input video streams, matching those vectors to codebook vector entries, and replacing them with indexes of the matched codebook vectors along with residual vectors to represent the difference between the input stream vector and the codebook vector. The combination of index and residual is generally smaller than the input stream vector which they collectively encode, thus providing compression. The improved codebook may be generated from training video streams by grouping together similar types of data (e.g., image data, motion data, control data) from the video stream to generate longer vectors having higher dimensions and greater structure. This improves the ability of VQ to remove redundancy and thus increase compression efficiency. Storage space is thus reduced and video transmission may be faster.
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公开(公告)号：US20210304706A1
公开(公告)日：2021-09-30
申请号：US16834776
申请日：2020-03-30
Applicant: Adobe Inc.
Inventor： Stefano Petrangeli , Viswanathan Swaminathan , Na Wang , Haoliang Wang , Gwendal Simon
IPC: G09G5/36 , G06F16/487 , G06F16/44
Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods that iteratively select versions of augmented reality objects at augmented reality levels of detail to provide for download to a client device to reduce start-up latency associated with providing a requested augmented reality scene. In particular, in one or more embodiments, the disclosed systems determine utility and priority metrics associated with versions of augmented reality objects associated with a requested augmented reality scene. The disclosed systems utilize the determined metrics to select versions of augmented reality objects that are likely to be viewed by the client device and improve the quality of the augmented reality scene as the client device moves through the augmented reality scene. In at least one embodiment, the disclosed systems iteratively select versions of augmented reality objects at various levels of detail until the augmented reality scene is fully downloaded.
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公开(公告)号：US20210279916A1
公开(公告)日：2021-09-09
申请号：US17331186
申请日：2021-05-26
Applicant: Adobe Inc.
Inventor： Gwendal Simon , Viswanathan Swaminathan , Nathan Carr , Stefano Petrangeli
IPC: G06T11/00 , H04N19/176 , H04N19/182 , G06T3/40
Abstract: Techniques and systems are provided for generating a video from texture images, and for reconstructing the texture images from the video. For example, a texture image can be divided into a number of tiles, and the number of tiles can be sorted into a sequence of ordered tiles. The sequence of ordered tiles can be provided to a video coder for generating a coded video. The number of tiles can be encoded based on the sequence of ordered tiles. The encoded video including the encoded sequence of ordered tiles can be decoded. At least a portion of the decoded video can include the number of tiles sorted into a sequence of ordered tiles. A data file associated with at least the portion of the decoded video can be used to reconstruct the texture image using the tiles.
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Patent Agency Ranking
公开(公告)号：US11115663B2
公开(公告)日：2021-09-07
申请号：US16295154
申请日：2019-03-07
Applicant: Adobe Inc.
Inventor： Viswanathan Swaminathan , Rashmi Mittal
IPC: H04N19/13 , H04N19/94 , H04N19/176 , H04N19/196
Abstract: Techniques are disclosed for the improvement of vector quantization (VQ) codebook generation. The improved codebooks may be used for compression in cloud-based video applications. VQ achieves compression by vectorizing input video streams, matching those vectors to codebook vector entries, and replacing them with indexes of the matched codebook vectors along with residual vectors to represent the difference between the input stream vector and the codebook vector. The combination of index and residual is generally smaller than the input stream vector which they collectively encode, thus providing compression. The improved codebook may be generated from training video streams by grouping together similar types of data (e.g., image data, motion data, control data) from the video stream to generate longer vectors having higher dimensions and greater structure. This improves the ability of VQ to remove redundancy and thus increase compression efficiency. Storage space is thus reduced and video transmission may be faster.
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公开(公告)号：US11049290B2
公开(公告)日：2021-06-29
申请号：US16584591
申请日：2019-09-26
Applicant: Adobe Inc.
Inventor： Gwendal Simon , Viswanathan Swaminathan , Nathan Carr , Stefano Petrangeli
IPC: G06T11/00 , G06T3/40 , H04N19/176 , H04N19/182
Abstract: Techniques and systems are provided for generating a video from texture images, and for reconstructing the texture images from the video. For example, a texture image can be divided into a number of tiles, and the number of tiles can be sorted into a sequence of ordered tiles. The sequence of ordered tiles can be provided to a video coder for generating a coded video. The number of tiles can be encoded based on the sequence of ordered tiles. The encoded video including the encoded sequence of ordered tiles can be decoded. At least a portion of the decoded video can include the number of tiles sorted into a sequence of ordered tiles. A data file associated with at least the portion of the decoded video can be used to reconstruct the texture image using the tiles.
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公开(公告)号：US20210037227A1
公开(公告)日：2021-02-04
申请号：US17074189
申请日：2020-10-19
Applicant: Adobe Inc.
IPC: H04N13/194 , H04N13/376
Abstract: In implementations of trajectory-based viewport prediction for 360-degree videos, a video system obtains trajectories of angles of users who have previously viewed a 360-degree video. The angles are used to determine viewports of the 360-degree video, and may include trajectories for a yaw angle, a pitch angle, and a roll angle of a user recorded as the user views the 360-degree video. The video system clusters the trajectories of angles into trajectory clusters, and for each trajectory cluster determines a trend trajectory. When a new user views the 360-degree video, the video system compares trajectories of angles of the new user to the trend trajectories, and selects trend trajectories for a yaw angle, a pitch angle, and a roll angle for the user. Using the selected trend trajectories, the video system predicts viewports of the 360-degree video for the user for future times.
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公开(公告)号：US10685236B2
公开(公告)日：2020-06-16
申请号：US16028352
申请日：2018-07-05
Applicant: Adobe Inc.
Inventor： Saayan Mitra , Viswanathan Swaminathan , Somdeb Sarkhel , Julio Alvarez Martinez, Jr.
Abstract: A metadata generation system utilizes machine learning techniques to accurately describe content of videos based on multi-model predictions. In some embodiments, multiple feature sets are extracted from a video, including feature sets showing correlations between additional features of the video. The feature sets are provided to a learnable pooling layer with multiple modeling techniques, which generates, for each of the feature sets, a multi-model content prediction. In some cases, the multi-model predictions are consolidated into a combined prediction. Keywords describing the content of the video are determined based on the multi-model predictions (or combined prediction). An augmented video is generated with metadata that is based on the keywords.
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20.发明申请公开(公告)号：US20190332971A1
公开(公告)日：2019-10-31
申请号：US15963737
申请日：2018-04-26
Applicant: Adobe Inc.
Inventor： Saayan Mitra , Xueyu Mao , Viswanathan Swaminathan , Somdeb Sarkhel , Sheng Li
Abstract: Techniques are disclosed for training of factorization machines (FMs) using a streaming mode alternating least squares (ALS) optimization. A methodology implementing the techniques according to an embodiment includes receiving a datapoint that includes a feature vector and an associated target value. The feature vector includes user identification, subject matter identification, and a context. The target value identifies an opinion of the user relative to the subject matter. The method further includes applying an FM to the feature vector to generate an estimate of the target value, and updating parameters of the FM for training of the FM. The parameter update is based on application of a streaming mode ALS optimization to: the datapoint; the estimate of the target value; and to an updated summation of intermediate calculated terms generated by application of the streaming mode ALS optimization to previously received datapoints associated with prior parameter updates of the FM.
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