Face and hand gesture recognition for human-computer interaction

Abstract

We propose a multi-camera system that can focus on faces and hand gestures for recognition. The system consists of four cameras. Two fixed cameras are used as a stereo system to estimate face and hand (F&H) positions. F&H regions are detected by a standard skin color method. The distances of the targets are then estimated. The positions and sizes of targets are evaluated for tracking between consecutive frames. The other two cameras perform tracking of such targets as faces and hands. If a target is not the appropriate size for recognition, the tracking cameras acquire its zoomed image. We propose a hierarchy linear discriminant analysis that distinguishes between faces and hands on the first step, and then recognizes face and hand gestures in each discriminant space by using four directional features. The experimental results show that our system could distinguish between faces and hands, as well as recognize face and hand gestures by using the four directional features.