Combining geometric- and view-based approaches for articulated pose estimation

Abstract

In this paper we propose an efficient real-time approach that combines vision-based tracking and a view-based model to estimate the pose of a person. We introduce an appearance model that contains views of a person under various articulated poses. The appearance model is built and updated online. The main contribution consists of modeling, in each frame, the pose changes as a linear transformation of the view change. This linear model allows (i) for predicting the pose in a new image, and (ii) for obtaining a better estimate of the pose corresponding to a key frame. Articulated pose is computed by merging the estimation provided by the tracking-based algorithm and the linear prediction given by the view-based model. © Springer-varlag 2004.