Human motion tracking method based on second generation Bandlet transform and top-speed learning machine

The invention discloses a human motion tracking method based on second generation Bandlet transform and top-speed learning machine, which is mainly used for solving the problems of inaccurate video image feature representation, high time complexity in regression function learning and inaccurate tracking result in the human motion tracking of the prior art. The realization process of the method comprises the following steps of: firstly, preprocessing the video image to obtain an original joint point three-dimensional coordinate matrix Y; extracting the second generation Bandlet 2 image feature X of the processed video image; taking the extracted Bandlet 2 image feature X as input, taking the three-dimensional coordinate matrix Y in the human body as the output, and using a top-speed learning machine to learn the regression function; using the regression function obtained by learning through the top-speed learning machine, taking the bandlet 2 feature X of the new video image as the input, estimating the three-dimensional attitude data of human body in motion. In comparison with the conventional human motion tracking method, the method provided by the invention is fast in the training process and accurate in image feature representation, and can be used for motion capture, man-machine interaction, video monitoring, human object recognition and three-dimensional attitude recovery.