PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Head and facial animation tracking using appearance-adaptive models and particle filters
Franck Davoine and F. Dornaika
In: Real-Time ision for Human Computer Interaction (2005) Springer Verlag . ISBN 0 387 27697 1

Abstract

In this chapter, we address the problem of tracking a face and its facial features in real video sequences, considering two approaches. The first approach is based on a particle filter tracker capable of tracking the 3D head pose of a person. In this case, the distribution of observations is derived from an eigenspace decomposition. The second approach introduces an appearance-adaptive tracker capable of tracking both the 3D head pose and facial animations. It consists of an online adapted observation model of the face texture, together with adaptive dynamics in the sense that they are guided by a deter- ministic search in a state space. This approach extends the concept of online appearance models to the case of tracking 3D non-rigid face motion (3D head pose and facial animations). Experiments on real video sequences show the eectiveness of the developed methods. Accurate tracking was obtained even in the presence of perturbing factors such as significant head pose or local facial occlusions.

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EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
User Modelling for Computer Human Interaction
Learning/Statistics & Optimisation
ID Code:1231
Deposited By:Franck Davoine
Deposited On:28 November 2005