Facial feature extraction and tracking in video sequences

In this paper, we describe a new approach for facial feature extraction. The features considered include eyes and mouth. A novel nonlinear filter is proposed for valley detection, which forms the low-level processing stage. A combination of temporal difference, color, image intensity and geometrical constraint is used to determine facial features in an initial frame. A temporal matching technique is used to track these features in the following frames. We also present a simple profile scanning method which can accurately locate special feature points such as corners in the eyes and mouth.