Extraction of spatial-temporal features for vision-based gesture recognition
One of the key problems in a vision-based gesture recognition system is the extraction of spatial-temporal features of gesturing. In this paper an approach of motion-based segmentation is proposed to realize this task. The direct method cooperated with the robust M-estimator to estimate the affine parameters of gesturing motion is used, and based on the dominant motion model the gesturing region is extracted, i.e., the dominant object. So the spatial-temporal features of gestures can be extracted. Finally, the dynamic time warping (DTW) method is directly used to perform matching of 12 control gestures (6 for "translation" orders, 6 for "rotation" orders). A small demonstration system has been set up to verify the method, in which a panorama image viewer can be controlled (set by mosaicing a sequence of standard "Garden" images) with recognized gestures instead of the 3-D mouse tool.
gesture recognition m-estimator dominant motion model affine transform model