Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 6, Issue 2


Published
on

November 22, 2021


Pages

127-138


DOI

Article

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

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Authors

Qingwen Chen Affiliation:
Department of Art, Shenzhen University, Shenzhen 518060, China
, Abdullah Albarakati Affiliation:
Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
and Lanlan Gui Affiliation:
Department of Art, Shenzhen University, Shenzhen 518060, China


Abstract

In order to verify the effectiveness and feasibility of the combination of motion capture technology and teaching, based on dance teaching, this paper proposes a dance posture analysis method based on feature vector matching and applies it to dance teaching.. The main research work includes the following: (1) according to the characteristics of human motion poses-free editing, extracting human skeleton models, establishing a human motion model database, analysing the application of motion capture systems in dance training, and proposing a method of feature plane similarity matching to calculate model components and motion parameters. After verification, the method has high accuracy and robustness for the 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 dance teaching method based on motion capture technology is proposed. Using motion capture technology, a whole complex dance movement is decomposed into many small segments to make a teaching animation, which guides students to learn based on small dance movement. Imitation makes the abstract theory vivid, intuitive and easy to understand, which is conducive for the innovation of education and teaching methods.


Keywords

posture analysis, motion capture, feature plane, similarity matching, dance teaching, 18F25


Citation

Chen, Q., Albarakati, A., & Gui, L. (2021). Research on motion capture of dance training pose based on statistical analysis of mathematical similarity matching. Applied Mathematics and Nonlinear Sciences, 6(2), 127–138. https://doi.org/10.2478/amns.2021.2.00053

Published by: Engineering Journals

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