Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022)

Dynamic Gait Recognition of Chinese Dance Based on Contour Features

Authors
Xiaoxuan Gong1, *
1Yunnan Institute of economics and management, Kunming, Yunnan, China
*Corresponding author. Email: 15484974@qq.com
Corresponding Author
Xiaoxuan Gong
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-040-4_195How to use a DOI?
Keywords
Contour feature; China classic dance; Gait recognition; Dynamic identification
Abstract

Single feature recognition has certain limitations, which can’t fully reflect the differences between dance gait information, resulting in low recognition rate of frame difference features. In this paper, a dynamic gait recognition method for Chinese classical dance is proposed based on contour features. The gait image of Chinese dance is preprocessed, the target region is segmented, and the gait cycle is extracted. The gait energy map is composed of the sequences in a cycle, which contains the information of the upper and lower limb motion frequencies of the dancer. The key distance, width, wavelet features and gait energy map are fused to form a group of feature vectors. The problem of low efficiency of single feature recognition is solved by feature fusion. Based on CNN model, a dynamic gait recognition model of Chinese dance is established based on contour features. Under the function of convolution kernel, the values of each channel are concatenated into a one-dimensional vector to express the contour features and complete the video sequence classification. The test results show that the design method retains the correlation between the gait data of Chinese classical dance, accurately locates the key points, and reflects the movement and time information of gait, so the recognition rate is improved.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
27 December 2022
ISBN
10.2991/978-94-6463-040-4_195
ISSN
2589-4900
DOI
10.2991/978-94-6463-040-4_195How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Xiaoxuan Gong
PY  - 2022
DA  - 2022/12/27
TI  - Dynamic Gait Recognition of Chinese Dance Based on Contour Features
BT  - Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022)
PB  - Atlantis Press
SP  - 1315
EP  - 1322
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-040-4_195
DO  - 10.2991/978-94-6463-040-4_195
ID  - Gong2022
ER  -