The value of kinematic modeling-based dance teaching methods in enhancing the effectiveness of complex movement training

The dance teaching method that effectively combines motion capture and posture estimation can effectively differentiate itself from the traditional dance teaching mode, realize the teaching interaction between the 3D virtual world and the real technology, and help to improve the quality of dance movement teaching.In this paper, HRNet network is selected under the framework of human posture estimation for the extraction of key points of human posture, and SPIN algorithm is composed of two parts, namely, regression network and SMPLify, to complete the three-dimensional expansion of human posture information.Design the flow of the dance visual movement tracking decomposition method, and perform feature point labeling and labeling parameter setting for multiple key points and key movement parts in the dance movement.Select the specific parts of the dancer as the motion tracking points, record and record the dancer's action images, and track and fit the dance action trajectory using the 3D visual motion tracking decomposition method proposed in this paper.Compare the dance trajectory fitting effect of this paper's method with that of the degree-of-freedom vector method and the tracking differentiator method, and obtain the performance of the three-dimensional visual motion tracking decomposition method.Analyze the students' physical flexibility, balance ability, and the completion of complex movements after a two-month dance teaching.After the dance teaching utilizing dance movement posture analysis, the students' body flexibility (shoulder) and balance ability improved by 12.8cm, 18.74s (left), and 22.2s (right), respectively.