Fast hand gesture recognition for real-time teleconferencing applications

Work on real-time hand-gesture recognition for SAVI (stereo active vision interface) is presented. Based on the detection of frontal faces, image regions near the face are searched for the existence of skin-tone blobs. Each blob is evaluated to determine if it it is a hand held in a standard pose. A verification algorithm based on the responses of elongated oriented filters is used to decide whether a hand is present or not. Once a hand is detected, gestures are given by varying the number of fingers visible. The hand is segmented using an algorithm which detects connected skin-tone blobs in the region of interest, and a medial axis transform (skeletonization) is applied. Analysis of the resulting skeleton allows detection of the number of fingers visible, thus determining the gesture. The skeletonization is sensitive to strong shadows which may alter the detected morphology of the hand. Experimental results are given indicating good performance of the algorithm