Robust 3D Face Tracking on Unknown Users with Dynamical Active Models

Authors:
Dianle Zhou;Patrick Horain
Affiliations:
Telecom & Management SudParis, Institut Telecom, ÉÉÉvry Cedex, France 91011;Telecom & Management SudParis, Institut Telecom, ÉÉÉvry Cedex, France 91011
Venue:
MMM '09 Proceedings of the 15th International Multimedia Modeling Conference on Advances in Multimedia Modeling
Year:
2009

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Abstract

The Active Appearance Models [1] and the derived Active Models (AM) [4] allow to robustly track the face of a single user that was previously learnt, but works poorly with multiple or unknown users. Our research aims at improving the tracking robustness by learning from video databases. In this paper, we study the relation between the face texture and the parameter gradient matrix, and propose a statistical approach to dynamically fit the AM to unknown users by estimating the gradient and update matrices from the face texture. We have implemented this algorithm for real time face tracking and experimentally demonstrate its robustness when tracking multiple or unknown users' faces.