Learning model for salient facial region detection

    公开(公告)号:US10579860B2

    公开(公告)日:2020-03-03

    申请号:US15449266

    申请日:2017-03-03

    Abstract: One embodiment provides a method comprising receiving a first input image and a second input image. Each input image comprises a facial image of an individual. For each input image, a first set of facial regions of the facial image is distinguished from a second set of facial regions of the facial image based on a learning based model. The first set of facial regions comprises age-invariant facial features, and the second set of facial regions comprises age-sensitive facial features. The method further comprises determining whether the first input image and the second input images comprise facial images of the same individual by performing face verification based on the first set of facial regions of each input image.

    System and method for fast object detection

    公开(公告)号:US11113507B2

    公开(公告)日:2021-09-07

    申请号:US15986689

    申请日:2018-05-22

    Abstract: One embodiment provides a method comprising identifying a salient part of an object in an input image based on processing of a region of interest (RoI) in the input image at an electronic device. The method further comprises determining an estimated full appearance of the object in the input image based on the salient part and a relationship between the salient part and the object. The electronic device is operated based on the estimated full appearance of the object.

    LEARNING MODEL FOR SALIENT FACIAL REGION DETECTION

    公开(公告)号:US20170351905A1

    公开(公告)日:2017-12-07

    申请号:US15449266

    申请日:2017-03-03

    Abstract: One embodiment provides a method comprising receiving a first input image and a second input image. Each input image comprises a facial image of an individual. For each input image, a first set of facial regions of the facial image is distinguished from a second set of facial regions of the facial image based on a learning based model. The first set of facial regions comprises age-invariant facial features, and the second set of facial regions comprises age-sensitive facial features. The method further comprises determining whether the first input image and the second input images comprise facial images of the same individual by performing face verification based on the first set of facial regions of each input image.

    Method and system for facial recognition

    公开(公告)号:US10776609B2

    公开(公告)日:2020-09-15

    申请号:US15905609

    申请日:2018-02-26

    Abstract: One embodiment provides a method for face liveness detection. The method comprises receiving a first image comprising a face of a user, determining one or more two-dimensional (2D) facial landmark points based on the first image, and determining a three-dimensional (3D) pose of the face in the first image based on the one or more determined 2D facial landmark points and one or more corresponding 3D facial landmark points in a 3D face model for the user. The method further comprises determining a homography mapping between the one or more determined 2D facial landmark points and one or more corresponding 3D facial landmark points that are perspectively projected based on the 3D pose, and determining liveness of the face in the first image based on the homography mapping.

    METHOD AND SYSTEM FOR FACIAL RECOGNITION
    7.
    发明申请

    公开(公告)号:US20190266388A1

    公开(公告)日:2019-08-29

    申请号:US15905609

    申请日:2018-02-26

    Abstract: One embodiment provides a method for face liveness detection. The method comprises receiving a first image comprising a face of a user, determining one or more two-dimensional (2D) facial landmark points based on the first image, and determining a three-dimensional (3D) pose of the face in the first image based on the one or more determined 2D facial landmark points and one or more corresponding 3D facial landmark points in a 3D face model for the user. The method further comprises determining a homography mapping between the one or more determined 2D facial landmark points and one or more corresponding 3D facial landmark points that are perspectively projected based on the 3D pose, and determining liveness of the face in the first image based on the homography mapping.

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