Human action recognition based on Kinect

With the emergence of Kinect, many research results have emerged in human action recognition based on skeleton information, which has promoted the development of human-computer interaction. In this paper, from the skeleton data obtained by Kinect, static features and dynamic features are extracted, and the two are merged; SVM classifier is used for action recognition. It is verified on the MSR Daily Activity 3D data set, and the experimental results show that the method in this paper improves the accuracy of action recognition.