摘要：We present a novel approach for 3D hand motion tracking of stage characteristics as observed in cognitive psychology. A Hidden Markov Model acquired in human-computer interaction is used to represent the high-level structure of gestures reduce the dimensionality of the search space. The estimation of hand gestures is handled by combing the model and particle filter. The sampling is introduced PERM instead of standard re-sampling to compensate the error caused by the observation model. The simulated experiment demonstrates significant improvements in tracking speed and robustness over comparison methods.
关键词：Hidden Markov Model; cognitive psychology; PERM; human hand tracking
