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Model-based and image-based methods for facial image synthesis, analysis and recognition

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3 Author(s)
Terzopoulos, D. ; Courant Inst. of Mathematical Sci., New York Univ., NY, USA ; Yuencheng Lee ; Vasilescu, M.A.O.

We review several model-based and image-based methods that we have developed for analyzing, synthesizing, and recognizing facial images. Our model-based methods include a sophisticated, functional model of the human face/head, which incorporates a biomechanical tissue model with embedded muscle actuators, and techniques for applying it to computer animation and expression estimation in video. Our image-based methods include tensor-faces, a nonlinear (multilinear) representation for facial image ensembles that disentangles pose, illumination, and expression effects to improve facial recognition.

Published in:

Automatic Face and Gesture Recognition, 2004. Proceedings. Sixth IEEE International Conference on

Date of Conference:

17-19 May 2004