Adaptive dynamic time warping for recognition of natural gestures

Abstract

Gesture recognition is one of the important tasks for human System Interaction (HRI). This paper describes a novel approach intended to recognize 3D dynamic composed gestures by combining Dynamic Time Warping (DTW) with an Adaptive Sliding Window which the name Adaptive Dynamic Time Warping (ADTW). We use the skeleton algorithm provided by the Kinect SDK to track the upper part of body and extract joints angles based on depth information. Each gesture is represented by the combination of angles variations and stored described as a vector. A composed gesture is a sequence of two simple gestures or more performed successively in time. We chose five simple gestures : come, recede, point to the right, point to the left and stop. For each simple gesture, we chose a reference sequence that perfectly represents it. In order to recognize all gesture of the composed gesture in the right order, we combine (DTW) with an Adaptive Sliding Window. In one hand, we use an adaptive window to browse through the sequence of the composed gesture by feeding it to each time with new data. In other hand, we use DTW to compare between the reference gestures and the the sequences defined by the adaptive window. In fact, by comparing each two sequences, DTW computes the euclidean distance between them. Finally, the reference gesture which gives the lower distance is considered as the source class of the tested gesture.