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    Avatar animation system
    2.
    发明授权
    Avatar animation system 有权

    公开(公告)号：US10475225B2

    公开(公告)日：2019-11-12

    申请号：US15124811

    申请日：2015-12-18

    Applicant: INTEL CORPORATION

    Inventor： Minje Park ,  Tae-Hoon Kim ,  Myung-Ho Ju ,  Jihyeon Yi ,  Xiaolu Shen ,  Lidan Zhang ,  Qiang Li

    IPC: G06T13/40 ,  G06T7/73 ,  G06T17/20

    Abstract: Avatar animation systems disclosed herein provide high quality, real-time avatar animation that is based on the varying countenance of a human face. In some example embodiments, the real-time provision of high quality avatar animation is enabled at least in part, by a multi-frame regressor that is configured to map information descriptive of facial expressions depicted in two or more images to information descriptive of a single avatar blend shape. The two or more images may be temporally sequential images. This multi-frame regressor implements a machine learning component that generates the high quality avatar animation from information descriptive of a subject's face and/or information descriptive of avatar animation frames previously generated by the multi-frame regressor. The machine learning component may be trained using a set of training images that depict human facial expressions and avatar animation authored by professional animators to reflect facial expressions depicted in the set of training images.

    AVATAR ANIMATION SYSTEM
    10.
    发明申请
    AVATAR ANIMATION SYSTEM 审中-公开

    公开(公告)号：US20200051306A1

    公开(公告)日：2020-02-13

    申请号：US16655686

    申请日：2019-10-17

    Applicant: INTEL CORPORATION

    Inventor： Minje Park ,  Tae-Hoon Kim ,  Myung-Ho Ju ,  Jihyeon Yi ,  Xiaolu Shen ,  Lidan Zhang ,  Qiang Li

    IPC: G06T13/40 ,  G06T7/73

    Abstract: Avatar animation systems disclosed herein provide high quality, real-time avatar animation that is based on the varying countenance of a human face. In some example embodiments, the real-time provision of high quality avatar animation is enabled at least in part, by a multi-frame regressor that is configured to map information descriptive of facial expressions depicted in two or more images to information descriptive of a single avatar blend shape. The two or more images may be temporally sequential images. This multi-frame regressor implements a machine learning component that generates the high quality avatar animation from information descriptive of a subject's face and/or information descriptive of avatar animation frames previously generated by the multi-frame regressor. The machine learning component may be trained using a set of training images that depict human facial expressions and avatar animation authored by professional animators to reflect facial expressions depicted in the set of training images.

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