公开(公告)号：US10311589B2

公开(公告)日：2019-06-04

申请号：US15823370

申请日：2017-11-27

Applicant: NVIDIA Corporation

Inventor： Gregory P. Meyer ,  Shalini Gupta ,  Iuri Frosio ,  Nagilla Dikpal Reddy ,  Jan Kautz

IPC: G06K9/00 ,  G06T7/507 ,  G06T7/70 ,  G06K9/62 ,  G06T7/73 ,  G06T7/77 ,  G06T7/246 ,  G06T7/277

Abstract: One embodiment of the present invention sets forth a technique for estimating a head pose of a user. The technique includes acquiring depth data associated with a head of the user and initializing each particle included in a set of particles with a different candidate head pose. The technique further includes performing one or more optimization passes that include performing at least one iterative closest point (ICP) iteration for each particle and performing at least one particle swarm optimization (PSO) iteration. Each ICP iteration includes rendering the three-dimensional reference model based on the candidate head pose associated with the particle and comparing the three-dimensional reference model to the depth data. Each PSO iteration comprises updating a global best head pose associated with the set of particles and modifying at least one candidate head pose. The technique further includes modifying a shape of the three-dimensional reference model based on depth data.

公开(公告)号：US09830703B2

公开(公告)日：2017-11-28

申请号：US14825129

申请日：2015-08-12

Applicant: NVIDIA CORPORATION

Inventor： Gregory P. Meyer ,  Shalini Gupta ,  Iuri Frosio ,  Nagilla Dikpal Reddy ,  Jan Kautz

IPC: G06K9/00 ,  G06T7/00

CPC classification number: G06T7/507 ,  G06K9/6276 ,  G06T7/251 ,  G06T7/277 ,  G06T7/70 ,  G06T7/75 ,  G06T7/77 ,  G06T2200/28 ,  G06T2207/10016 ,  G06T2207/10028 ,  G06T2207/30201

Abstract: One embodiment of the present invention sets forth a technique for estimating a head pose of a user. The technique includes acquiring depth data associated with a head of the user and initializing each particle included in a set of particles with a different candidate head pose. The technique further includes performing one or more optimization passes that include performing at least one iterative closest point (ICP) iteration for each particle and performing at least one particle swarm optimization (PSO) iteration. Each ICP iteration includes rendering the three-dimensional reference model based on the candidate head pose associated with the particle and comparing the three-dimensional reference model to the depth data. Each PSO iteration comprises updating a global best head pose associated with the set of particles and modifying at least one candidate head pose. The technique further includes modifying a shape of the three-dimensional reference model based on depth data.