Hand Gesture Modeling Using Dynamic Bayesian Networks and Deformable Templates

The paper presents a stochastic approach to articulated hand (palm shape) tracking in images. The gesture model is given in terms of a Dynamic Bayesian network that incorporates a Hidden Markov Model in order to utilize prior information on gesture structure in the tracking task. The Deformable Templates methodology is applied for hand shape modeling. Experimental evaluation of articulated hand tracking in cluttered environment using particle filtering is provided. A comparison of this method with a typical tracking approach, that makes no use of temporal gesture information, is also given.