Spatio-Temporal Appearance Modeling and Recognition of Continuous Dynamic Hand Gestures

This paper presents the segmentation, spatio temporal appearance modeling and recognition of continuous dynamic hand gestures with complex background. Fusing the coarse motion information and skin color chrominance, the segmentation of hand gesture can be got robustly. By integrating temporal information, motion appearance, and shape appearance, a spatio temporal appearance model is proposed to represent dynamic hand gestures, and a novel scheme is proposed for recovering the model parameters by hierarchical fusion of multi modal information such as skin chrominance, motion, and shape. In addition, Dynamic Space Time Warping is suggested for recognition of hand gestures. Experiment results indicate that the average recognition rate of the 12 hand gestures is 97% based on the proposed segmentation, modeling, feature extracting, and recognition techniques.