3D Expressive face model-based tracking algorithm
SPPRA'06 Proceedings of the 24th IASTED international conference on Signal processing, pattern recognition, and applications
Analysis of head and facial gestures using facial landmark trajectories
BioID_MultiComm'09 Proceedings of the 2009 joint COST 2101 and 2102 international conference on Biometric ID management and multimodal communication
Facial expression recognition based on anatomy
Computer Vision and Image Understanding
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We propose a simple framework that utilizes online appearance models for 3D face and facial feature tracking with a deformable model. Adapting the geometrical parameters for each frame adopts a steepest ascent method in the observation likelihood using a local exhaustive and directed search in the parameter space. The observation likelihood is based on the current appearance and the registered images. The developed framework is straightforward and has the following advantages. First, it does not require any a priori statistical facial texture. Second, it does not require any a priori transition model for the 3D motion. Video sequences featuring large head motions, large facial animations, and external illumination variations are successfully tracked, which demonstrate the efficiency of the developed framework.