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research in International Biometrics Journal Introducing a new method for assessing practitioner accuracy in martial arts training. This method focuses on quickly identifying errors in an athlete's movements and allowing trainers to more accurately guide athletes to correct form.
The system was developed with a particular focus on Wushu, a collection of Chinese martial arts styles known for their complexity and precision.
Zhiqiang Li from the Police Sports Education Research Department of Jilin Police University in Changchun, China, explains how the system used advanced algorithms such as optical flow methods and shot-adaptive K-means clustering. These are used to extract “key frames” from the video and analyze the textural features of martial arts movements.
Through analysis, the accuracy of detecting false movements reaches 96.58%. He adds that the minimum recognition error is 1.9%. Importantly, this method is highly efficient and provides positive feedback for trainers and students in as little as 11 seconds.
This approach can be very useful in martial arts training, allowing coaches to identify mistakes in real-time and give students on-the-spot advice and advice, even when mistakes are hard to spot or decisions are vague in class. Be able to provide guidance.
Therefore, this method could increase the effectiveness of training and could also reduce the number of physical problems faced by students, given that wrong actions often lead to injuries. High precision not only helps students improve their technical proficiency, but also makes participation in martial arts safer. This system also benefits the overall aesthetic appeal of martial arts performance.
One might imagine that this system could be extended to referee purposes when it is unclear whether a technique or movement is permitted or illegal in a particular martial art. It is also easy to imagine that such a system would be as controversial as the digital linesmen used in international tennis or the Video Assistant Referee (VAR) used in soccer (association).
For more information:
Zhiqiang Li, How to recognize martial arts athletes' wrong actions based on keyframe extraction, International Biometrics Journal (2024). DOI: 10.1504/IJBM.2024.138228
Magazine information:
International Biometrics Journal