METHODS AND SYSTEMS FOR HAND GESTURE-BASED CONTROL OF A DEVICE

    公开(公告)号:US20230082789A1

    公开(公告)日:2023-03-16

    申请号:US17950246

    申请日:2022-09-22

    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.

    SELF-SUPERVISED VIDEO REPRESENTATION LEARNING BY EXPLORING SPATIOTEMPORAL CONTINUITY

    公开(公告)号:US20230072445A1

    公开(公告)日:2023-03-09

    申请号:US17468224

    申请日:2021-09-07

    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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