Joint modeling of facial expression and shape from video

Abstract

In this paper, we present a novel model for representing facial feature point tracks during an facial expression. The model is composed of a static shape part and a time-dependent expression part. We learn the model by tracking the points of interest in video recordings of trained actors making different facial expressions. Our results indicate that the proposed sum of two linear models - a person-dependent shape model and a person-independent expression model - approximates the true feature point motion well. © Springer-Verlag Berlin Heidelberg 2005.