Real-time gesture recognition using KL expansion of image sequence

This paper presents a method of real time gesture recognition from image sequences. Real time gesture recognition is required for man machine interfaces and many multimedia applications. Our method recognizes a user's gesture in a low dimensional 'gesture space' which is constituted by Karhunen-Loeve (KL) expansion of model image sequences. We first segment a human part image in real time using the maskable template model which is an improved template matching method for gesture recognition. The segmented image sequence is represented as a gesture curve in the gesture space, and gesture is recognized by analyzing the curve. Using our method, we realize a real time interactive system, the Virtual Conductor System, which can control music played by a computer using gesture recognition results and indicates the usefulness of our method.