• Journal of Information Processing Systems
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• v.18 no.6
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• pp.813-821
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• 2022

Intelligent monitoring, life entertainment, medical rehabilitation, and other fields are only a few examples where visual image technology is becoming increasingly sophisticated and playing a significant role. Recognizing Wushu, or martial arts, movements through the use of visual image technology helps promote and develop Wushu. In order to segment and extract the signals of Wushu movements, this study analyzes the denoising of the original data using the wavelet transform and provides a sliding window data segmentation technique. Wushu movement The Wushu movement recognition model is built based on the hidden Markov model (HMM). The HMM model is trained and taught with the help of the Baum-Welch algorithm, which is then enhanced using the frequency weighted training approach and the mean training method. To identify the dynamic Wushu movement, the Viterbi algorithm is used to determine the probability of the optimal state sequence for each Wushu movement model. In light of the foregoing, an HMM-based martial arts movements recognition model is developed. The recognition accuracy of the HMM model increases to 99.60% when the number of samples is 4,000, which is greater than the accuracy of the SVM (by 0.94%), the CNN (by 1.12%), and the BP (by 1.14%). From what has been discussed, it appears that the suggested system for detecting martial arts acts is trustworthy and effective, and that it may contribute to the growth of martial arts.

• International Journal of Advanced Culture Technology
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• v.12 no.2
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• pp.438-447
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• 2024

The subjects of this study were college students who participate in Wushu in China. A total of 300 people, 189 male and 111 female, were sampled as research subjects through convenience sampling by sharing the questionnaire link online and sending emails. The research tool used in this study was a questionnaire. Based on the questionnaire that had secured reliability and validity in previous research, it was modified and supplemented to suit this study. The statistical analysis used for data analysis was frequency analysis, exploratory factor analysis, reliability analysis, and multiple regression analysis using SPSS Windows 20.0 Version. First, Wushu image was found to have a partial effect on self-congruity. Second, Wushu image was found to have a partial effect on loyalty. Third, the self-congruity of Wushu participants was found to partially affect loyalty.