A Robust Facial Feature Tracking Method Based on Optical Flow and Prior Measurement

Authors:
Guoyin Wang;Yong Yang;Kun He
Affiliations:
Chonggqing University of Posts and Telecommunications, China;Chonggqing University of Posts and Telecommunications, China;Tencent Corporation, China
Venue:
International Journal of Cognitive Informatics and Natural Intelligence
Year:
2010

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Abstract

Cognitive informatics CI is a research area including some interdisciplinary topics. Visual tracking is not only an important topic in CI, but also a hot topic in computer vision and facial expression recognition. In this paper, a novel and robust facial feature tracking method is proposed, in which Kanade-Lucas-Tomasi KLT optical flow is taken as basis. The prior method of measurement consisting of pupils detecting features restriction and errors and is used to improve the predictions. Simulation experiment results show that the proposed method is superior to the traditional optical flow tracking. Furthermore, the proposed method is used in a real time emotion recognition system and good recognition result is achieved.