Hand Gesture Recognition Using Time-of-Flight Camera and Viewpoint Feature Histogram

Time-of-flight (ToF) cameras acquire 3D information about observed scenes. They are increasingly used for hand gesture recognition. This paper is also related to this problem. In contrast to other works which try to segment the hands we propose using point cloud processing and the Viewpoint Feature Histogram (VFH) as the global descriptor of the scene. To empower the distinctiveness of the descriptor a modification is proposed which consists in dividing the work space into smaller cells and calculating the VFH for each of them. The method is applied to five sample static gestures which are relatively difficult to recognise because hands are not the objects nearest the camera and/or touch each other, touch the head or appear in the background of the face. Results of tenfold cross validation that justify the proposed approach are given.