Multi-cue Facial Feature Detection and Tracking

Authors:
Jingying Chen;Bernard Tiddeman
Affiliations:
School of Computer Science, University of St Andrews, Fife, Scotland, UK KY16 9SX;School of Computer Science, University of St Andrews, Fife, Scotland, UK KY16 9SX
Venue:
ICISP '08 Proceedings of the 3rd international conference on Image and Signal Processing
Year:
2008

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Abstract

An efficient and robust facial feature detection and tracking system is presented in this paper. The system is capable of locating a human face automatically. Six facial feature points (pupils, nostrils and mouth corners) are detected and tracked using multiple cues including facial feature intensity and its probability distribution, geometric characteristics and motion information. In addition, in order to improve the robustness of the tracking system, a simple facial feature model is employed to estimate the relative face poses. This system has the advantage of automatically detecting the facial features and recovering the features lost during the tracking process. Encouraging results have been obtained using the proposed system.