Simulated annealing based hand tracking in a discrete space

Abstract

Hand tracking is a challenging problem due to the complexity of searching in a 20+ degrees of freedom (DOF) space for an optimal estimation of hand configuration. This paper represents the feasible hand configurations as a discrete space, which avoids learning to find parameters as general configuration space representations do. Then, we propose an extended simulated annealing method with particle filter to search for optimal hand configuration in this discrete space, in which simplex search running in multi-processor is designed to predict the hand motion instead of initializing the simulated annealing randomly, and particle filter is employed to represent the state of the tracker at each layer for searching in high dimensional configuration space. The experimental results show that the proposed method makes the hand tracking more efficient and robust. © Springer-Verlag Berlin Heidelberg 2005.