Title: Recognition method of dance rotation based on multi-feature fusion

Authors: Yang Liu; Meiyan Fan; Wenfeng Xu

Addresses: College of Physical Education and Art, Jilin Physical Education College, Changchun 130-000, Jilin, China ' College of Physical Education and Art, Jilin Physical Education College, Changchun 130-000, Jilin, China ' College of Physical Education and Art, Jilin Physical Education College, Changchun 130-000, Jilin, China

Abstract: There are some problems in traditional dance rotation recognition methods, such as low accuracy of contour superposition and low recognition rate. A dance rotation recognition method based on multi-feature fusion is proposed. The background noise subtraction method is used to separate the human motion regions in the foreground of the video data, and the contour features of each frame image of the preprocessed dance video are superimposed to obtain the direction gradient histogram features of the dance action information. According to the law of optical flow, the feature vectors of the histogram of optical flow direction are normalised. According to the shape and motion characteristics of human dance in dance video, the dance rotation recognition classifier is constructed to complete the dance rotation recognition based on multi-feature fusion. The experimental results show that the proposed method has higher accuracy of 97% and lower error rate of 0.7%.

Keywords: multi-feature fusion; mesh division; directional gradient; optical flow field.

DOI: 10.1504/IJART.2021.10043501

International Journal of Arts and Technology, 2021 Vol.13 No.2, pp.91 - 107

Received: 26 Nov 2020
Accepted: 19 Apr 2021

Published online: 21 Jan 2022 *

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