Title: Research on emotion recognition method of weightlifters based on a non-negative matrix decomposition algorithm

Authors: Qiang Wu

Addresses: Department of Sport, Xiamen University of Technology, Xiamen, Fujian, 361024, China

Abstract: In order to overcome the problems of high recognition error rate and low recognition efficiency existing in the traditional method of emotional recognition of weightlifters, a method of emotional recognition of weightlifters based on a non-negative matrix decomposition algorithm is proposed. The database of emotion recognition matching criteria is established, and the mapping relationship among emotion, facial expression of far mobilisation and weight lifting posture is formed. The real-time motion images of weightlifters are collected, and the image classifier is designed by using the non-negative matrix decomposition algorithm. The real-time images are divided into facial expression images and whole body motion images, and the features of the two images are extracted respectively. The extracted results are matched with the results of the standard database, and the real-time emotion recognition results of weightlifters are obtained. The experimental results show that compared with the traditional emotion recognition method, the proposed method improves the accuracy of emotion recognition by 50%.

Keywords: non-negative matrix decomposition algorithm; weightlifter; athlete emotion; mapping relationship; dimension reduction.

DOI: 10.1504/IJBM.2021.114650

International Journal of Biometrics, 2021 Vol.13 No.2/3, pp.229 - 242

Received: 02 Apr 2020
Accepted: 30 Jun 2020
Published online: 29 Apr 2021 *

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