A gait recognition method for a moving target image in sports based on a decision tree

Abstract

In order to overcome the low accuracy of traditional gait recognition methods, a new gait recognition method based on a decision tree is proposed. The decision tree classification method is used to obtain the effective gait features in the sports target image. Based on the acquired effective gait features, the weighted block sparse representation method is used to realise the gait recognition of the sports target image. The experimental results show that this method has high recognition accuracy for the gait in the sports target image with small area occlusion and no occlusion. When the dimension is 301, the recognition accuracy of this method is 97.5%. Compared with similar recognition methods, the recognition accuracy of this method is significant and can be used in the task of gait recognition of a sports target image.