Segment action detection
    11.
    发明授权

    公开(公告)号:US11704893B2

    公开(公告)日:2023-07-18

    申请号:US17465001

    申请日:2021-09-02

    Applicant: Snap Inc.

    Abstract: Aspects of the present disclosure involve a system comprising a storage medium storing a program and method for receiving a video comprising a plurality of video segments; selecting a target action sequence that includes a sequence of action phases; receiving features of each of the video segments; computing, based on the received features, for each of the plurality of video segments, a plurality of action phase confidence scores indicating a likelihood that a given video segment includes a given action phase of the sequence of action phases; identifying a set of consecutive video segments of the plurality of video segments that corresponds to the target action sequence, wherein video segments in the set of consecutive video segments are arranged according to the sequence of action phases; and generating a display of the video that includes the set of consecutive video segments and skips other video segments in the video.

    Segment action detection
    12.
    发明授权

    公开(公告)号:US11158351B1

    公开(公告)日:2021-10-26

    申请号:US16228120

    申请日:2018-12-20

    Applicant: Snap Inc.

    Abstract: Aspects of the present disclosure involve a system comprising a storage medium storing a program and method for receiving a video comprising a plurality of video segments; selecting a target action sequence that includes a sequence of action phases; receiving features of each of the video segments; computing, based on the received features, for each of the plurality of video segments, a plurality of action phase confidence scores indicating a likelihood that a given video segment includes a given action phase of the sequence of action phases; identifying a set of consecutive video segments of the plurality of video segments that corresponds to the target action sequence, wherein video segments in the set of consecutive video segments are arranged according to the sequence of action phases; and generating a display of the video that includes the set of consecutive video segments and skips other video segments in the video.

    EFFICIENT HUMAN POSE TRACKING IN VIDEOS

    公开(公告)号:US20210125342A1

    公开(公告)日:2021-04-29

    申请号:US16949594

    申请日:2020-11-05

    Applicant: Snap Inc.

    Abstract: Systems, devices, media and methods are presented for a human pose tracking framework. The human pose tracking framework may identify a message with video frames, generate, using a composite convolutional neural network, joint data representing joint locations of a human depicted in the video frames, the generating of the joint data by the composite convolutional neural network done by a deep convolutional neural network operating on one portion of the video frames, a shallow convolutional neural network operating on a another portion of the video frames, and tracking the joint locations using a one-shot learner neural network that is trained to track the joint locations based on a concatenation of feature maps and a convolutional pose machine. The human pose tracking framework may store, the joint locations, and cause presentation of a rendition of the joint locations on a user interface of a client device.

    Neural network-based image stream modification

    公开(公告)号:US10679428B1

    公开(公告)日:2020-06-09

    申请号:US15990318

    申请日:2018-05-25

    Applicant: Snap Inc.

    Abstract: Systems, devices, media, and methods are presented for object detection and inserting graphical elements into an image stream in response to detecting the object. The systems and methods detect an object of interest in received frames of a video stream. The systems and methods identify a bounding box for the object of interest and estimate a three-dimensional position of the object of interest based on a scale of the object of interest. The systems and methods generate one or more graphical elements having a size based on the scale of the object of interest and a position based on the three-dimensional position estimated for the object of interest. The one or more graphical elements are generated within the video stream to form a modified video stream. The systems and methods cause presentation of the modified video stream including the object of interest and the one or more graphical elements.

    Body pose estimation
    16.
    发明授权

    公开(公告)号:US12136158B2

    公开(公告)日:2024-11-05

    申请号:US18060449

    申请日:2022-11-30

    Applicant: Snap Inc.

    Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for detecting a pose of a user. The program and method include receiving a monocular image that includes a depiction of a body of a user; detecting a plurality of skeletal joints of the body depicted in the monocular image; and determining a pose represented by the body depicted in the monocular image based on the detected plurality of skeletal joints of the body. A pose of an avatar is modified to match the pose represented by the body depicted in the monocular image by adjusting a set of skeletal joints of a rig of an avatar based on the detected plurality of skeletal joints of the body; and the avatar having the modified pose that matches the pose represented by the body depicted in the monocular image is generated for display.

    BODY POSE ESTIMATION
    18.
    发明申请

    公开(公告)号:US20230090086A1

    公开(公告)日:2023-03-23

    申请号:US18060449

    申请日:2022-11-30

    Applicant: Snap Inc.

    Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for detecting a pose of a user. The program and method include receiving a monocular image that includes a depiction of a body of a user; detecting a plurality of skeletal joints of the body depicted in the monocular image; and determining a pose represented by the body depicted in the monocular image based on the detected plurality of skeletal joints of the body. A pose of an avatar is modified to match the pose represented by the body depicted in the monocular image by adjusting a set of skeletal joints of a rig of an avatar based on the detected plurality of skeletal joints of the body; and the avatar having the modified pose that matches the pose represented by the body depicted in the monocular image is generated for display.

    Body pose estimation
    19.
    发明授权

    公开(公告)号:US11557075B2

    公开(公告)日:2023-01-17

    申请号:US17212555

    申请日:2021-03-25

    Applicant: Snap Inc.

    Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for detecting a pose of a user. The program and method include receiving a monocular image that includes a depiction of a body of a user; detecting a plurality of skeletal joints of the body depicted in the monocular image; and determining a pose represented by the body depicted in the monocular image based on the detected plurality of skeletal joints of the body. A pose of an avatar is modified to match the pose represented by the body depicted in the monocular image by adjusting a set of skeletal joints of a rig of an avatar based on the detected plurality of skeletal joints of the body; and the avatar having the modified pose that matches the pose represented by the body depicted in the monocular image is generated for display.

    3D HAND SHAPE AND POSE ESTIMATION
    20.
    发明申请

    公开(公告)号:US20220414985A1

    公开(公告)日:2022-12-29

    申请号:US17823764

    申请日:2022-08-31

    Applicant: Snap Inc.

    Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and a method for receiving a monocular image that includes a depiction of a hand and extracting features of the monocular image using a plurality of machine learning techniques. The program and method further include modeling, based on the extracted features, a pose of the hand depicted in the monocular image by adjusting skeletal joint positions of a three-dimensional (3D) hand mesh using a trained graph convolutional neural network (CNN); modeling, based on the extracted features, a shape of the hand in the monocular image by adjusting blend shape values of the 3D hand mesh representing surface features of the hand depicted in the monocular image using the trained graph CNN; and generating, for display, the 3D hand mesh adjusted to model the pose and shape of the hand depicted in the monocular image.

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