Mathematical analysis of human motion vision capture image processing based on artificial intelligence

In order to understand the mathematical analysis of human motion vision capture image processing, a mathematical analysis of human motion vision capture image processing based on artificial intelligence is proposed. This paper firstly introduces the research progress, classification and several commonly used vision-based human motion tracking methods of motion capture technology. Secondly, the process and framework of capturing human motion video by using ordinary cameras and marking nodes are proposed, and the automatic tracking algorithm based on Camshift and Kalman filter is adopted. It verifies the effectiveness of the system, changes the traditional way of motion capture, and makes the process of capture more convenient when the capture effect meets the requirements. Finally, the performance of the human motion capture data retrieval algorithm based on video is evaluated comprehensively. It is compared with the latest literature in this field. In terms of time efficiency, for each online retrieval of data set, the proposed algorithm takes 0.056 s, while the methods of other scholars take an average of 1.5 s. Meanwhile, experiments are also conducted on public databases, proving the universality and scalability of the proposed algorithm. The algorithm proposed in this paper has greater advantages than the most advanced method of the same type, which verifies the effectiveness of the algorithm proposed in this paper.