Detecting Faces in Color Images Using an Adaptive Color Model and Salient Features

Face detection has many interesting applications such as a face recognition system, a surveillance system, and videolimage indexing system. In this paper, we propose a new method of face detection using an adaptive skin color model and salient features. First, we detect skin color segments by adjusting threshold window in HueSaturation(HS) subspace based on the distribution of color histogram. From the detected skin color segments, salient feature points like eyes for face are extracted. After that, the possible eye feature points are compared with normalized eye features which are obtained from the training data. At this template matching stage, we use a modified Hausdorff distance. Finally, eye feature points are selected and then face segments are determined. Experimental results are presented.