Single camera pointing gesture recognition using spatial features and support vector machines

In this paper, a method for recognizing pointing gestures without markers is proposed. The video-based system uses one camera, which observes the user in front of a screen and identifies the points pointed by him on this screen, his arm being in the fully extended position towards the screen. A GVF-snake was used in order to find the silhouette of the user. From the silhouette features like position where the person is standing, the position of the fingertip, and the position of the shoulder are extracted, tracked and used to construct a feature vector for each video frame. This vector is fed to properly trained multi-class support vector machines (SVM) in order to obtain the 2D position of the target point on the screen. Two different camera setups with different feature vector configurations are proposed and tested. Experiments show very promising results for recognizing the pointing gestures by using a single camera.