Research on motion capture of dance training pose based on statistical analysis of mathematical similarity matching

• Autores: Qingwen Chen, Abdullah Albarakati, Lanlan Gui
• Localización: Applied Mathematics and Nonlinear Sciences, ISSN-e 2444-8656, Vol. 7, Nº. 2, 2022, págs. 127-138
• Idioma: inglés
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• Resumen

  • In order to verify the effectiveness and feasibility of the combination of motion capture technology and teaching, basedon dance teaching, this paper proposes a dance posture analysis method based on feature vector matching and appliesit to dance teaching.. The main research work includes the following: (1) according to the characteristics of humanmotion poses-free editing, extracting human skeleton models, establishing a human motion model database, analysing theapplication of motion capture systems in dance training, and proposing a method of feature plane similarity matching tocalculate model components and motion parameters. After verification, the method has high accuracy and robustness forthe analysis of human posture, so that dancers can accurately compare the differences with standard dance movements,and provide theoretical support for scientific dance training. (2) Aiming at the complexity of learning dance, a danceteaching method based on motion capture technology is proposed. Using motion capture technology, a whole complexdance movement is decomposed into many small segments to make a teaching animation, which guides students to learnbased on small dance movement. Imitation makes the abstract theory vivid, intuitive and easy to understand, which isconducive for the innovation of education and teaching methods