Using Machine Learning Algorithms to Recognize Shuttlecock Movements

Abstract

Shuttlecock is an excellent traditional national sport in China. Because of its simplicity, convenience, and fun, it is loved by the broad masses of people, especially teenagers and children. The development of shuttlecock sports into a confrontational event is not long, and it takes a period of research to master the tactics and strategies of shuttlecock sports. Based on this, this article proposes the use of machine learning algorithms to recognize the movement of shuttlecock movements, aiming to provide more theoretical and technical support for shuttlecock competitions by identifying features through actions with the assistance of technical algorithms. This paper uses literature research methods, model methods, comparative analysis methods, and other methods to deeply study the motion characteristics of shuttlecock motion, the key algorithms of machine learning algorithms, and other theories and construct the shuttlecock motion recognition based on multiview clustering algorithm. The model analyzes the robustness and accuracy of the machine learning algorithm and other algorithms, such as a variety of performance comparisons, and the results of the shuttlecock motion recognition image. For the key movements of shuttlecock movement, disk, stretch, hook, wipe, knock, and abduction, the algorithm proposed in this paper has a good movement recognition rate, which can reach 91.2%. Although several similar actions can be recognized well, the average recognition accuracy rate can exceed 75%, and even through continuous image capture, the number of occurrences of the action can be automatically analyzed, which is beneficial to athletes. And the coach can better analyze tactics and research strategies.

Changes in Physical Function of Shuttlecock Players after Short-Term Intensive Training based on Data Mining

“…Because of its simplicity, convenience, and fun, it is loved by the majority of people, especially teenagers and children. Before long, badminton has developed into a confrontational sport, and it takes a period of research to master badminton's tactics and strategies [ 3 ]. According to Chen et al, motion video analysis has been gaining popularity recently because of its importance in understanding motion and improving athlete performance [ 4 ].…”

Effects of 15 weeks of Jianzi training on the physical fitness and physiological functions of university female students

“…In addition, Shuttlecock players must be able to change direction quickly based on the circumstances of the game while maintaining a constant focus on their opponent or ball Al-wahid et al (2022). Therefore, increasing speed and agility is a must for every training program shuttlecock (Wang, 2021). SMC responded to the growing exercise needs of female students at Agu-VNU-HCM and achieved results in speed and agility that were superior to the current program in this study.…”

A court line extraction algorithm for badminton tournament videos with horizontal line projection learning

“…It is essential to develop the sophisticated content‐based analysis techniques for retrieving sport videos efficiently. The researches on sport video analysis have increased largely [1‐23]. The paper [23] has done a comprehensive review of computer vision in sports.…”

“…In addition, due to the simplicity and the convenience of badminton, badminton is one of the most popular rocket sports in the world now [8]. According to the BWF (Badminton World Federation) event calendar [24], there are 195 and 154 tournaments in years 2022 and 2023, respectively.…”

“…According to the BWF (Badminton World Federation) event calendar [24], there are 195 and 154 tournaments in years 2022 and 2023, respectively. However, there are less number of papers in researching into the badminton videos since they have more challenges [8][9][10][11][12]22]. For example, the small-size shuttlecock moves in high speed in playing badminton and the court field is more compact.…”