Recognition of signed dynamic expressions observed by ToF camera

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, hand segmentation based, works 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 chosen dynamic gestures of the Polish sign language. The gestures are relatively difficult to recognise because the hands often 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 ten-fold cross-validation for the nearest neighbour classifier based on dynamic time warping for sequence comparison are given to justify the proposed approach.