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公开(公告)号:US20180350105A1
公开(公告)日:2018-12-06
申请号:US15994563
申请日:2018-05-31
Applicant: Google LLC
Inventor: Jonathan James TAYLOR , Vladimir TANKOVICH , Danhang TANG , Cem KESKIN , Adarsh Prakash Murthy KOWDLE , Philip L. DAVIDSON , Shahram IZADI , David KIM
CPC classification number: G06T7/75 , G06K9/00382 , G06T7/149 , G06T7/162 , G06T7/194 , G06T7/251 , G06T2207/10016 , G06T2207/10028 , G06T2207/20076 , G06T2207/20081
Abstract: An electronic device estimates a pose of a hand by volumetrically deforming a signed distance field using a skinned tetrahedral mesh to locate a local minimum of an energy function, wherein the local minimum corresponds to the hand pose. The electronic device identifies a pose of the hand by fitting an implicit surface model of a hand to the pixels of a depth image that correspond to the hand. The electronic device uses a skinned tetrahedral mesh to warp space from a base pose to a deformed pose to define an articulated signed distance field from which the hand tracking module derives candidate poses of the hand. The electronic device then minimizes an energy function based on the distance of each corresponding pixel to identify the candidate pose that most closely approximates the pose of the hand.
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公开(公告)号:US20180350087A1
公开(公告)日:2018-12-06
申请号:US15994509
申请日:2018-05-31
Applicant: Google LLC
Inventor: Adarsh Prakash Murthy KOWDLE , Vladimir TANKOVICH , Danhang TANG , Cem KESKIN , Jonathan James Taylor , Philip L. DAVIDSON , Shahram IZADI , Sean Ryan FANELLO , Julien Pascal Christophe VALENTIN , Christoph RHEMANN , Mingsong DOU , Sameh KHAMIS , David KIM
IPC: G06T7/593 , G06T7/32 , G06T7/33 , H04N13/271
CPC classification number: G06T7/521 , G06T7/593 , G06T2207/10021 , G06T2207/10024 , G06T2207/10152 , G06T2207/20072 , G06T2207/20076 , G06T2207/20081
Abstract: An electronic device estimates a depth map of an environment based on stereo depth images captured by depth cameras having exposure times that are offset from each other in conjunction with illuminators pulsing illumination patterns into the environment. A processor of the electronic device matches small sections of the depth images from the cameras to each other and to corresponding patches of immediately preceding depth images (e.g., a spatio-temporal image patch “cube”). The processor computes a matching cost for each spatio-temporal image patch cube by converting each spatio-temporal image patch into binary codes and defining a cost function between two stereo image patches as the difference between the binary codes. The processor minimizes the matching cost to generate a disparity map, and optimizes the disparity map by rejecting outliers using a decision tree with learned pixel offsets and refining subpixels to generate a depth map of the environment.
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