Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 8, Issue 2


Published
on

October 30, 2023


Pages


DOI

Article

Research on the Analysis of Traditional Dance Performance Forms and Dance Movement Characteristics Based on Artificial Intelligence Technology

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Authors

Hui He Affiliation:
Conservatory of Music, Zhangjiakou University, Zhangjiakou, Hebei, 075000, China.
, Baoyu Wang Affiliation:
School of Education, Zhangjiakou University, Zhangjiakou, Hebei, 075000, China.
and Jing Chang Affiliation:
Conservatory of Music, Zhangjiakou University, Zhangjiakou, Hebei, 075000, China.


Abstract

This paper analyzes the performance forms and movement characteristics of traditional dances by using the method of movement feature extraction. We construct a dance key movement extraction system by merging optical flow computing and extracting the key movements of music and dance, which increases the efficiency of traditional dance movement analysis and reduces computational complexity. We can improve the similarity matching of human posture when using picture entropy computation. It uses an optical capture technique to record lively dancing motions. The results show that the accuracy of optical flow computation is 0.8 for distinguishing the form of the cultural lion performance, 0.85 for distinguishing the martial lion performance, 0.75 for distinguishing the aerial lion performance, and 0.6 for capturing the tumbling movement of the cultural lion and 0.7 for capturing the frolicking movement under the optical motion capture system.


Keywords

Image entropy calculation, Optical flow calculation, Action feature extraction, Dance performance form, Lion dance, 91E45


Citation

He, H., Wang, B., & Chang, J. (2023). Research on the analysis of traditional dance performance forms and dance movement characteristics based on artificial intelligence technology. Applied Mathematics and Nonlinear Sciences, 8(2). https://doi.org/10.2478/amns.2023.2.00856

Published by: Engineering Journals

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