Realtime visual tracking system with two cameras for feature recognition of moving human face

There is a tradeoff between magnification and viewing width when recognizing features on a moving object, for example, eyes or a mouth of a human who is moving around. To recognize an image feature precisely or correctly, we need to have enough resolution of the image. It is not easy, however, to keep the feature area steady and centered in the camera's image if the object with the feature on moving fast or far away. This paper presents a visual tracking method for feature recognition of moving human face. We use two cameras with different viewing-angles to catch information both with lower resolution for tracking a moving object and with higher resolution for object recognition. The statistical information of the difference image between successive frames will be used to estimate the motion speed of a moving object. To demonstrate the idea of this visual tracking system, we show its application to our anthropomorphous agent system called VSA (visual software agent), which is an advanced human interface system with a realistic human facial image and a speech communication function.