Precision Extraction Algorithm of Three-dimensional Human Gait Motionfeature

In this artical a new algorithm based on super-pixel is proposed to extract the gait feature of human body. Firstly, the feature points of human gait motion are segmented, and the energy function of the segmentation process is minimized. The multivariate statistical model is used to accurately estimate the noise related information of the segmented gait motion features, and the noiseless coding of fractal wavelet is set to reconstruct the 3D human gait motion feature signals. The feature noise of human gait motion is removed efficiently. The experimental results show that the proposed algorithm is superior to the current algorithm in the enhancement and feature extraction of human gait motion, and the energy consumption of the proposed algorithm is about 70% lower than that of the current method, which can provide a reference for the further study of human gait motion.