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    FACIAL EXPRESSION AND/OR INTERACTION DRIVEN AVATAR APPARATUS AND METHOD
    2.
    发明申请
    FACIAL EXPRESSION AND/OR INTERACTION DRIVEN AVATAR APPARATUS AND METHOD 审中-公开
    FACIAL表达和/或交互驱动的AVATAR装置和方法

    公开(公告)号：US20160042548A1

    公开(公告)日：2016-02-11

    申请号：US14416580

    申请日：2014-03-19

    Applicant: INTEL CORPORATION

    Inventor： Yangzhou DU ,  Tae-Hoon KIM ,  Wenlong LI ,  Qiang LI ,  Xiaofeng TONG ,  Tao WANG ,  Minje PARK ,  Olivier DUCHENNE ,  Yimin ZHANG ,  Yeongjae CHEON ,  Bongjin JUN ,  Wooju RYU ,  Thomas SACHSON ,  Mary D. SMILEY

    IPC: G06T13/40 ,  G06T7/20 ,  G06T15/00 ,  G06K9/00

    CPC classification number: G06T13/40 ,  G06K9/00308 ,  G06K9/00315 ,  G06K9/00335 ,  G06K2009/4666 ,  G06T7/251 ,  G06T15/005 ,  G06T2200/04 ,  G06T2207/10016 ,  G06T2207/30201

    Abstract: Apparatuses, methods and storage medium associated with animating and rendering an avatar are disclosed herein. In embodiments, an apparatus may include a facial mesh tracker to receive a plurality of image frames, detect facial action movements of a face and head pose gestures of a head within the plurality of image frames, and output a plurality of facial motion parameters and head pose parameters that depict facial action movements and head pose gestures detected, all in real time, for animation and rendering of an avatar. The facial action movements and head pose gestures may be detected through inter-frame differences for a mouth and an eye, or the head, based on pixel sampling of the image frames. The facial action movements may include opening or closing of a mouth, and blinking of an eye. The head pose gestures may include head rotation such as pitch, yaw, roll, and head movement along horizontal and vertical direction, and the head comes closer or goes farther from the camera. Other embodiments may be described and/or claimed.

    Abstract translation: 本文公开了与动画和呈现化身相关联的装置，方法和存储介质。 在实施例中，装置可以包括面部网格跟踪器，用于接收多个图像帧，检测多个图像帧内的头部的脸部和头部姿势手势的面部动作运动，并且输出多个面部运动参数和头部 构成参数，其描绘了所有实时检测到的面部动作动作和头部姿势手势，用于动画和呈现头像。 基于图像帧的像素采样，可以通过口和眼或头部的帧间差异来检测面部动作运动和头部姿势手势。 面部动作动作可以包括开口或闭合嘴，以及眼睛的眨眼。 头部姿势手势可以包括水平和垂直方向的头部旋转，例如俯仰，偏航，滚动和头部移动，并且头部靠近或离开相机更远。 可以描述和/或要求保护其他实施例。

    CONTINUOUS LEARNING FOR OBJECT TRACKING
    3.
    发明申请
    CONTINUOUS LEARNING FOR OBJECT TRACKING 有权

    公开(公告)号：US20210312642A1

    公开(公告)日：2021-10-07

    申请号：US17057084

    申请日：2019-01-03

    Applicant: Intel Corporation

    Inventor： Lidan ZHANG ,  Ping GUO ,  Haibing REN ,  Yimin ZHANG

    IPC: G06T7/246 ,  G06K9/62 ,  G06N20/00

    Abstract: A long-term object tracker employs a continuous learning framework to overcome drift in the tracking position of a tracked object. The continuous learning framework consists of a continuous learning module that accumulates samples of the tracked object to improve the accuracy of object tracking over extended periods of time. The continuous learning module can include a sample pre-processor to refine a location of a candidate object found during object tracking, and a cropper to crop a portion of a frame containing a tracked object as a sample and to insert the sample into a continuous learning database to support future tracking.

    OBJECT IDENTIFICATION BASED ON ADAPTIVE LEARNING
    4.
    发明公开
    OBJECT IDENTIFICATION BASED ON ADAPTIVE LEARNING 审中-公开

    公开(公告)号：US20230206612A1

    公开(公告)日：2023-06-29

    申请号：US17999709

    申请日：2020-06-24

    Applicant: Intel Corporation

    Inventor： Sangeeta Ghangam MANEPALLI ,  Siew Wen CHIN ,  Ping GUO ,  Qi SHE ,  Yingzhe SHEN ,  Lidan ZHANG ,  Yimin ZHANG

    IPC: G06V10/80 ,  G06V40/16 ,  G06V10/774 ,  G06V10/776 ,  G06V10/62

    CPC classification number: G06V10/809 ,  G06V10/62 ,  G06V10/774 ,  G06V10/776 ,  G06V40/161

    Abstract: Disclosed herein are systems, methods, and devices for using adaptive learning to identify objects. An object-identifying device performs a first object identification based on one or more features of a first modality of an object retrieved from an image frame including the object and a first database including first modality identification features. A second object identification is performed based on one or more features of a second modality of the object retrieved from the image frame and a second database including second modality identification features. The second database is updated by adaptively learning a new second modality identification feature according to a first identification result of the first object identification. The second object identification is trained with the updated second database and determines a final identification result by integrating a first identification result of the first object identification and a second identification result of the second object identification.

    METHODS AND APPARATUS TO MATCH IMAGES USING SEMANTIC FEATURES
    6.
    发明申请
    METHODS AND APPARATUS TO MATCH IMAGES USING SEMANTIC FEATURES 有权

    公开(公告)号：US20210174134A1

    公开(公告)日：2021-06-10

    申请号：US16768559

    申请日：2018-03-01

    Applicant: Intel Corporation

    Inventor： Yimin ZHANG ,  Haibing REN ,  Wei HU ,  Ping GUO

    IPC: G06K9/62 ,  G06K9/46 ,  G06K9/32

    Abstract: Methods and apparatus to match images using semantic features are disclosed. An example apparatus includes a semantic labeler to determine a semantic label for each of a first set of points of a first image and each of a second set of points of a second image; a binary robust independent element features (BRIEF) determiner to determine semantic BRIEF descriptors for a first subset of the first set of points and a second subset of the second set of points based on the semantic labels; and a point matcher to match first points of the first subset of points to second points of the second subset of points based on the semantic BRIEF descriptors.

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