Classifying the motions of human body by using Gabor wavelets

Describes a method for classifying the motions of human bodies in an image sequence. First a set of templates is prepared in advance, which includes the spatio-temporal Gabor wavelet expansion coefficients of key motions. Next, processing is performed to obtain the Gabor wavelet expansion coefficients of an unknown motion. Matching factors between the expansion coefficients of both the key motions and the unknown motions are then calculated, and finally the unknown motion is classified as one of the key motions. Experimental results using image sequences from a volleyball game show the effectiveness of the proposed method