A method of athlete foul action recognition based on DTW algorithm

There may be various foul actions in different sports events, which vary in form, speed, and rhythm, increasing the difficulty of action recognition. Therefore, a DTW algorithm based athlete foul action recognition method is proposed. Select the OV7670 camera to collect athlete action images, extract image contour information, and use it as a feature of athlete foul actions. Based on the collected images, evenly sample the contours of the images to obtain contour feature points. Optimise the DTW algorithm from three aspects: reference template modelling, distortion calculation, and determining the optimal path. Use the extracted action feature sequence as the input of the DTW algorithm to output the recognition results of athlete foul actions. The experimental results show that the distortion of this method is as low as 0.58, indicating that it can accurately identify athlete foul actions and has high application value.

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Publication Details

Journal
International Journal of Biometrics
Published
2025-01-01
DOI
https://doi.org/10.1504/ijbm.2025.143725
Citations
1
Primary Topic
Anomaly Detection Techniques and Applications
Type
article
Field-Weighted Citation Impact
2.48
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article

A method of athlete foul action recognition based on DTW algorithm

Weihai Zhong, Chuan Wang, Yanpeng Zhao, Cheng Yang
1 citations
International Journal of Biometrics
Anomaly Detection Techniques and Applications
2.48
article

A method of athlete foul action recognition based on DTW algorithm

Weihai Zhong, Chuan Wang, Yanpeng Zhao, Cheng Yang
article en
1 citations

Abstract

There may be various foul actions in different sports events, which vary in form, speed, and rhythm, increasing the difficulty of action recognition. Therefore, a DTW algorithm based athlete foul action recognition method is proposed. Select the OV7670 camera to collect athlete action images, extract image contour information, and use it as a feature of athlete foul actions. Based on the collected images, evenly sample the contours of the images to obtain contour feature points. Optimise the DTW algorithm from three aspects: reference template modelling, distortion calculation, and determining the optimal path. Use the extracted action feature sequence as the input of the DTW algorithm to output the recognition results of athlete foul actions. The experimental results show that the distortion of this method is as low as 0.58, indicating that it can accurately identify athlete foul actions and has high application value.

International Journal of BiometricsVol. 17(1/2)
Dalian University of Foreign Languages (CN), Shandong University of Science and Technology (CN)
Openalex Percentile: Top 12%
Anomaly Detection Techniques and Applications
2.48
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