We propose a model-based tracking method, called appearance-guided particle filtering (AGPF), which integrates both sequential motion transition information and appearance information. A probability propagation model is derived from a Bayesian formulation for this framework, and a sequential Monte Carlo method is introduced for its realization. We apply the proposed method to articulated hand tracking, and show that it performs better than methods that only use either sequential motion transition information or only use appearance information.
Appearance-guided particle filtering for articulated hand tracking
01.01.2005
747209 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Model-based 3D tracking of an articulated hand
IEEE | 2001
|Tracking Articulated Hand Motion with Eigen Dynamics Analysis
British Library Conference Proceedings | 2003
|Model-Based 3D Tracking of an Articulated Hand
British Library Conference Proceedings | 2001
|Attractor-Guided Particle Filtering for Lip Contour Tracking
British Library Conference Proceedings | 2006
|