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公开(公告)号：US20210152739A1
公开(公告)日：2021-05-20
申请号：US17159984
申请日：2021-01-27
Applicant: Huawei Technologies Co., Ltd.
Abstract: Methods and devices for generating a slow motion video segment are described. A first set of video frames captures a video view at a first resolution and at a first frame rate. A second set of video frames captures the video view at a second lower resolution, and at a second frame rate that is greater for at least a portion of the second set. At least two high resolution frames are identified in the first set for generating the slow motion video segment. One or more low resolution frames are identified in the second set corresponding to an inter-frame time period between the identified high resolution frames. The slow motion video segment is generated by generating at least one high resolution frame corresponding to the inter-frame time period using interpolation based on the identified high resolution frames and the identified low resolution frames.
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Patent Agency Ranking
公开(公告)号：US20240292073A1
公开(公告)日：2024-08-29
申请号：US18656705
申请日：2024-05-07
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Md Ibrahim KHALIL , Peng DAI , Hanwen LIANG , Lizhe CHEN , Varshanth Ravindra RAO , Juwei LU , Songcen XU
IPC: H04N21/8549 , G06F3/0484 , G06V10/70 , G06V20/40
CPC classification number: H04N21/8549 , G06V10/70 , G06V20/46 , G06V20/49 , G06F3/0484
Abstract: Methods and devices for generating a customized video segment from a video are disclosed. The video is partitioned into video segments. For each respective video segment, a respective set of scores is computed, where each score represents a respective content feature in the respective video segment. A respective weighted aggregate score is computed for each respective video segment by applying, to each respective set of scores, a common set of weight values. A selected video segment is outputted as the customized video segment, where the selected video segment is selected from one or more high-ranked video segments having high-ranked weighted aggregate scores.
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公开(公告)号：US20230350499A1
公开(公告)日：2023-11-02
申请号：US18345794
申请日：2023-06-30
Applicant: Huawei Technologies Co., Ltd.
Inventor： Juwei LU , Sayem Mohammad SIAM , Deepak SRIDHAR , Sidharth SINGLA , Yannick VERDIE , Xiaofei WU , Srikanth MURALIDHARAN , Roy YANG , Peng DAI , Songcen XU
CPC classification number: G06F3/017 , G06V40/28 , G06V40/10 , G06V20/46 , G06T7/70 , G06T2207/10016
Abstract: Methods and devices for machine vision-based selection of content are described. One or more hands are detected in a current frame of video data. A respective fingertip location is determined for each of up to two of the detected hands. A content selection gesture is determined corresponding to the up to two detected hands. Selected content is extracted, as indicated by the content selection gesture and based on the up to two fingertip locations. The device may be a smartphone, a tablet, a laptop, a smart light device, a reader device, etc.
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公开(公告)号：US20230082789A1
公开(公告)日：2023-03-16
申请号：US17950246
申请日：2022-09-22
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Juwei LU , Sayem Mohammad SIAM , Wei ZHOU , Peng DAI , Xiaofei WU , Songcen XU
Abstract: Methods and systems for gesture-based control of a device are described. An input frame is processed to determine a location of a distinguishing anatomical feature in the input frame. A virtual gesture-space is defined based on the location of the distinguishing anatomical feature, the virtual gesture-space being a defined space for detecting a gesture input. The input frame is processed in only the virtual gesture-space, to detect and track a hand. Using information generated from detecting and tracking the at least one hand, a gesture class is determined for the at least one hand. The device may be a smart television, a smart phone, a tablet, etc.
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5.发明公开公开(公告)号：US20230281981A1
公开(公告)日：2023-09-07
申请号：US18315866
申请日：2023-05-11
Applicant: Huawei Technologies Co., Ltd.
Inventor： Xin DING , Deepak SRIDHAR , Juwei LU , Sidharth SINGLA , Peng DAI , Xiaofei WU
IPC: G06V10/82 , G06V10/776
CPC classification number: G06V10/82 , G06V10/776
Abstract: Method and devices for training a keypoint estimation network are described. In each training iteration, synthetic images are generated by a generator, each synthetic image being assigned respective assigned keypoints by the generator. Using a prior-iteration of the keypoint estimation network, a set of predicted keypoints is obtained for each synthetic image. Based on an error score between the predicted keypoints and the assigned keypoints, poor quality synthetic images are discarded. The remaining synthetic images, together with real world images, are used to train an updated keypoint estimation network. The performance of the updated keypoint estimation network is validated, and the training iterations are performed until a convergence criteria is satisfied.
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公开(公告)号：US20230072445A1
公开(公告)日：2023-03-09
申请号：US17468224
申请日：2021-09-07
Applicant: HUAWEI TECHNOLOGIES CO., LTD.
Inventor： Hanwen LIANG , Peng DAI , Zhixiang CHI , Lizhe CHEN , Juwei LU
Abstract: This disclosure provides a training method and apparatus, and relates to the artificial intelligence field. The method includes feeding a primary video segment, representative of a concatenation of a first and a second nonadjacent video segments obtained from a video source, to a deep learning backbone network. The method further includes embedding, via the deep learning backbone network, the primary video segment into a first feature output. The method further includes providing the first feature output to a first perception network to generate a first set of probability distribution outputs indicating a temporal location of a discontinuous point associated with the primary video segment. The method further includes generating a first loss function based on the first set of probability distribution outputs. The method further includes optimizing the deep learning backbone network, by backpropagation of the first loss function.
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