Article: Dynamic segmentation algorithm of dance video image for non-legacy ethnic dance inheritance Journal: International Journal of Information and Communication Technology (IJICT) 2025 Vol.26 No.47 pp.106 - 127 Abstract: Traditional manual arrangement struggles to efficiently handle complex backgrounds, frequent movements and variable lighting in dance videos; high-precision automatic techniques are urgently needed for digital analysis and protection. In this paper, a large-scale dance video dataset covering multi-ethnic, multi-scene and multi-illumination conditions is constructed, and the preliminary extraction of foreground region is realised by using the motion detection module combining frame difference method and optical flow method. Then, based on the improved U-Net structure, multi-scale feature fusion and attention mechanism are designed to enhance the segmentation ability of clothing and limb details, and the joint loss of Dice and cross entropy is used to improve the boundary accuracy. Experimental results show that the proposed method is better than U-Net and DeepLabv3+ in terms of IoU, Dice, precision, recall, F1-score, etc., and shows stronger robustness and near real-time processing speed in complex scenes. Inderscience Publishers - linking academia, business and industry through research

Title: Dynamic segmentation algorithm of dance video image for non-legacy ethnic dance inheritance

Authors: Xiaoyu Zhang

Addresses: School of Fashion, Henan University of Engineering, No. 1 Xianghe Road, Longhu Town, Xinzheng City, Zhengzhou, 450000, Henan Province, China

Abstract: Traditional manual arrangement struggles to efficiently handle complex backgrounds, frequent movements and variable lighting in dance videos; high-precision automatic techniques are urgently needed for digital analysis and protection. In this paper, a large-scale dance video dataset covering multi-ethnic, multi-scene and multi-illumination conditions is constructed, and the preliminary extraction of foreground region is realised by using the motion detection module combining frame difference method and optical flow method. Then, based on the improved U-Net structure, multi-scale feature fusion and attention mechanism are designed to enhance the segmentation ability of clothing and limb details, and the joint loss of Dice and cross entropy is used to improve the boundary accuracy. Experimental results show that the proposed method is better than U-Net and DeepLabv3+ in terms of IoU, Dice, precision, recall, F1-score, etc., and shows stronger robustness and near real-time processing speed in complex scenes.

Keywords: intangible cultural heritage; ethnic dance; video image processing; dynamic segmentation algorithm.

DOI: 10.1504/IJICT.2025.150599

International Journal of Information and Communication Technology, 2025 Vol.26 No.47, pp.106 - 127

Received: 30 Sep 2025
Accepted: 28 Oct 2025
Published online: 17 Dec 2025 *

Title: Dynamic segmentation algorithm of dance video image for non-legacy ethnic dance inheritance

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