3D Expressive Face Model-based Tracking Algorithm

M. Anisetti, V. Bellandi, E. Damiani, and F. Beverina (Italy)


Face Tracking, Candide-3, FACS, Emotion Recognition


This paper presents a method for tracking a face on a video sequence, by recovering the full-motion and the expres sion deformation of the face using 3D expressive facial model. From some characteristic face points given on the first frame, an approximated 3D model of the face is re constructed. Using a steepest descent image approach, the algorithm is able to extract simultaneously the parameters related to the face expression and to the 3D posture. The algorithm has been tested on the Kanade-Cohn database [1] and its precision has been compared with a standard multi camera system for the 3D tracking (ELITE2002 System). The results in both cases are good. The proposed approach is part of a facial expression analysis system. Our aim is to detect the facial expressions in situations characterized by a moderate head motion in realistic experimental conditions (illumination from the ceiling, and subjects not in frontal pose).

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