Appearance-guided particle filtering for articulated hand tracking

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 C...

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Bibliographic Details
Published in2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) Vol. 1; pp. 235 - 242 vol. 1
Main Authors Wen-Yan Chang, Chu-Song Chen, Yi-Ping Hung
Format Conference Proceeding
LanguageEnglish
Published IEEE 2005
Subjects
Filtering algorithms
Information filtering
Information filters
Motion estimation
Nonlinear dynamical systems
Particle tracking
State estimation
State-space methods
Stochastic processes
Target tracking
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Summary: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.
ISBN:0769523722
9780769523729
ISSN:1063-6919
1063-6919
DOI:10.1109/CVPR.2005.72