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公开(公告)号：US11438549B2
公开(公告)日：2022-09-06
申请号：US17294568
申请日：2018-11-22
Applicant: Polycom, Inc.
Inventor： Tianran Wang , Wenxue He , Lidan Qin , Hai Xu
IPC: H04N7/15 , G06V40/10 , G06T7/20 , H04L12/18 , H04L65/1083
Abstract: A videoconferencing endpoint is described that uses a combination of face detection, motion detection, and upper body detection for selecting participants of a videoconference for group framing. Motion detection is used to remove fake faces as well as to detect motion in regions around detected faces during postprocessing. Upper body detection is used in conjunction with the motion detection in postprocessing to allow saving faces that have been initially detected by face detection for group framing even if the participant has turned away from the camera, allowing the endpoint to keep tracking the participants region better than would be possible based only on an unstable result coming from face detection.
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公开(公告)号：US20220006974A1
公开(公告)日：2022-01-06
申请号：US17294568
申请日：2018-11-22
Applicant: Polycom, Inc.
Inventor： Tianran Wang , Wenxue He , Lidan Qin , Hai Xu
Abstract: A videoconferencing endpoint is described that uses a combination of face detection, motion detection, and upper body detection for selecting participants of a videoconference for group framing. Motion detection is used to remove fake faces as well as to detect motion in regions around detected faces during postprocessing. Upper body detection is used in conjunction with the motion detection in postprocessing to allow saving faces that have been initially detected by face detection for group framing even if the participant has turned away from the camera, allowing the endpoint to keep tracking the participants region better than would be possible based only on an unstable result coming from face detection.
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公开(公告)号：US20210409645A1
公开(公告)日：2021-12-30
申请号：US17294573
申请日：2018-11-22
Applicant: Polycom, Inc.
Inventor： Hai Xu , Xi Lu , Yongkang Fan , Wenxue He
Abstract: A videoconferencing endpoint is described that uses a cascading sequence of convolutional neural networks to perform face detection and upper body detection of participants in a videoconference at the endpoint, where at least one member of the sequence of neural networks performs upper body detection, and where the final member of the sequence of neural networks performs face detection based on the results of the upper body detection. The models of the neural networks are trained on both large datasets of faces well as images that have been distorted by a wide-angle camera of the videoconferencing endpoint.
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