DocumentCode :
3021852
Title :
Model-based and image-based methods for facial image synthesis, analysis and recognition
Author :
Terzopoulos, Demetri ; Lee, Yuencheng ; Vasilescu, M. Alex O
Author_Institution :
Courant Inst. of Mathematical Sci., New York Univ., NY, USA
fYear :
2004
fDate :
17-19 May 2004
Firstpage :
3
Lastpage :
8
Abstract :
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.
Keywords :
computer animation; face recognition; biomechanical tissue model; computer animation; embedded muscle actuators; face image analysis; face image recognition; facial image synthesis; image-based methods; model-based methods; tensor-faces; Actuators; Face recognition; Facial animation; Head; Humans; Image analysis; Image generation; Image recognition; Lighting; Muscles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automatic Face and Gesture Recognition, 2004. Proceedings. Sixth IEEE International Conference on
Print_ISBN :
0-7695-2122-3
Type :
conf
DOI :
10.1109/AFGR.2004.1301501
Filename :
1301501
Link To Document :
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