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Patent Agency Ranking
公开(公告)号：US20210174519A1
公开(公告)日：2021-06-10
申请号：US16709128
申请日：2019-12-10
Applicant: Google LLC
Inventor： Valentin Bazarevsky , Fan Zhang , Andrei Vakunov , Andrei Tkachenka , Matthias Grundmann
Abstract: Example aspects of the present disclosure are directed to computing systems and methods for hand tracking using a machine-learned system for palm detection and key-point localization of hand landmarks. In particular, example aspects of the present disclosure are directed to a multi-model hand tracking system that performs both palm detection and hand landmark detection. Given a sequence of image frames, for example, the hand tracking system can detect one or more palms depicted in each image frame. For each palm detected within an image frame, the machine-learned system can determine a plurality of hand landmark positions of a hand associated with the palm. The system can perform key-point localization to determine precise three-dimensional coordinates for the hand landmark positions. In this manner, the machine-learned system can accurately track a hand depicted in the sequence of images using the precise three-dimensional coordinates for the hand landmark positions.
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公开(公告)号：US11783496B2
公开(公告)日：2023-10-10
申请号：US17527463
申请日：2021-11-16
Applicant: Google LLC
Inventor： Valentin Bazarevsky , Fan Zhang , Andrei Vakunov , Andrei Tkachenka , Matthias Grundmann
CPC classification number: G06T7/251 , G06T7/75 , G06V40/28 , G06T2207/20081 , G06T2207/30196
Abstract: Example aspects of the present disclosure are directed to computing systems and methods for hand tracking using a machine-learned system for palm detection and key-point localization of hand landmarks. In particular, example aspects of the present disclosure are directed to a multi-model hand tracking system that performs both palm detection and hand landmark detection. Given a sequence of image frames, for example, the hand tracking system can detect one or more palms depicted in each image frame. For each palm detected within an image frame, the machine-learned system can determine a plurality of hand landmark positions of a hand associated with the palm. The system can perform key-point localization to determine precise three-dimensional coordinates for the hand landmark positions. In this manner, the machine-learned system can accurately track a hand depicted in the sequence of images using the precise three-dimensional coordinates for the hand landmark positions.
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公开(公告)号：US11182909B2
公开(公告)日：2021-11-23
申请号：US16709128
申请日：2019-12-10
Applicant: Google LLC
Inventor： Valentin Bazarevsky , Fan Zhang , Andrei Vakunov , Andrei Tkachenka , Matthias Grundmann
Abstract: Example aspects of the present disclosure are directed to computing systems and methods for hand tracking using a machine-learned system for palm detection and key-point localization of hand landmarks. In particular, example aspects of the present disclosure are directed to a multi-model hand tracking system that performs both palm detection and hand landmark detection. Given a sequence of image frames, for example, the hand tracking system can detect one or more palms depicted in each image frame. For each palm detected within an image frame, the machine-learned system can determine a plurality of hand landmark positions of a hand associated with the palm. The system can perform key-point localization to determine precise three-dimensional coordinates for the hand landmark positions. In this manner, the machine-learned system can accurately track a hand depicted in the sequence of images using the precise three-dimensional coordinates for the hand landmark positions.
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公开(公告)号：US20230410329A1
公开(公告)日：2023-12-21
申请号：US18460338
申请日：2023-09-01
Applicant: Google LLC
Inventor： Valentin Bazarevsky , Fan Zhang , Andrei Tkachenka , Andrei Vakunov , Matthias Grundmann
CPC classification number: G06T7/251 , G06T7/75 , G06V40/28 , G06T2207/30196 , G06T2207/20081
Abstract: Example aspects of the present disclosure are directed to computing systems and methods for hand tracking using a machine-learned system for palm detection and key-point localization of hand landmarks. In particular, example aspects of the present disclosure are directed to a multi-model hand tracking system that performs both palm detection and hand landmark detection. Given a sequence of image frames, for example, the hand tracking system can detect one or more palms depicted in each image frame. For each palm detected within an image frame, the machine-learned system can determine a plurality of hand landmark positions of a hand associated with the palm. The system can perform key-point localization to determine precise three-dimensional coordinates for the hand landmark positions. In this manner, the machine-learned system can accurately track a hand depicted in the sequence of images using the precise three-dimensional coordinates for the hand landmark positions.
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公开(公告)号：US20220076433A1
公开(公告)日：2022-03-10
申请号：US17527463
申请日：2021-11-16
Applicant: Google LLC
Inventor： Valentin Bazarevsky , Fan Zhang , Andrei Vakunov , Andrei Tkachenka , Matthias Grundmann
Abstract: Example aspects of the present disclosure are directed to computing systems and methods for hand tracking using a machine-learned system for palm detection and key-point localization of hand landmarks. In particular, example aspects of the present disclosure are directed to a multi-model hand tracking system that performs both palm detection and hand landmark detection. Given a sequence of image frames, for example, the hand tracking system can detect one or more palms depicted in each image frame. For each palm detected within an image frame, the machine-learned system can determine a plurality of hand landmark positions of a hand associated with the palm. The system can perform key-point localization to determine precise three-dimensional coordinates for the hand landmark positions. In this manner, the machine-learned system can accurately track a hand depicted in the sequence of images using the precise three-dimensional coordinates for the hand landmark positions.
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