Dance Motion Detection Algorithm Based on Computer Vision

posture recognition is an essential link in the development of human-computer interaction. Currently, the existing dance movement training methods often require students to constantly watch videos or find a tutor to correct them during practice to achieve good results, which not only takes a lot of time and energy but also creates some difficulties and challenges for students. The research goal of this paper was to use computer recognition technology to detect dance movements and identify body postures. This paper develops a Kinect dance auxiliary training system based on the body skeleton tracking technology of the Kinect 3D sensor, combined with auxiliary dance training. This article not only introduced a fixed axis-based expression method for joint angles to improve the stability of joint angles but also improved the body position detection algorithm using the angle of joint spots to realize the accurate recognition of human body posture. In the experiment, the trainee's arm was raised to the highest position, which could not meet the requirements, and the trainer's wrist should be raised by another 200 mm. Moreover, retracting the hand was too fast, which did not meet the standard action. The test results showed that the system could effectively improve the dance movements of the students.