A framework for modeling the appearance of 3D articulated figures - Robotics Institute Carnegie Mellon University

A framework for modeling the appearance of 3D articulated figures

H. Sidenbladh, F. De la Torre, and M. J. Black
Conference Paper, Proceedings of 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG '00), pp. 368 - 375, March, 2000

Abstract

This paper describes a framework for constructing a linear subspace model of image appearance for complex articulated 3D figures such as humans and other animals. A commercial motion capture system provides 3D data that is aligned with images of subjects performing various activities. Portions of a limb's image appearance are seen from multiple views and for multiple subjects. From these partial views, weighted principal component analysis is used to construct a linear subspace representation of the "unwrapped" image appearance of each limb. The linear subspaces provide a generative model of the object appearance that is exploited in a Bayesian particle filtering tracking system. Results of tracking single limbs and walking humans are presented.

BibTeX

@conference{Sidenbladh-2000-120964,
author = {H. Sidenbladh and F. De la Torre and M. J. Black},
title = {A framework for modeling the appearance of 3D articulated figures},
booktitle = {Proceedings of 4th IEEE International Conference on Automatic Face and Gesture Recognition (FG '00)},
year = {2000},
month = {March},
pages = {368 - 375},
}
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