Robust Facial Feature Tracking Under Various Illuminations

An efficient and robust facial tracking system is presented in this paper. The system is capable of distinguishing a human face from a complex background using motion and histogram based methods. We correct for variations in illumination using a mixture of local and global illumination balance techniques. We detect and track six facial feature points i.e. pupils, nostrils and lip corners using facial feature illumination, geometric characteristics and motion information. In addition, a 3D facial feature model is employed to estimate the 3D pose of the subject´s head, which improves the robustness of the tracking system. 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.