Motion recognition technology of badminton players in sports video images

Fang, Lei; Sun, Mingsi

doi:10.1016/j.future.2021.05.036

Cited by 22 publications

(15 citation statements)

References 25 publications

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“…In the sports events field, there are many excellent cases for early solutions using image processing for the detection of specific targets. For example, Fang and Sun [ 20 ] had researched human motion recognition techniques in the images of a dancing video. They proposed a new cfrdF method based on example templates, which used Cascading Style Sheet (CSS)-based human feature similarity as a feature, then devised an adaptive angle and continuous-scale spatial matching algorithm, and finally calculated the similarity between the horizontal plate and the detected image value; after setting the threshold value, the region of the human body could be matched.…”

Section: Related Workmentioning

confidence: 99%

Table Tennis Track Detection Based on Temporal Feature Multiplexing Network

Liu

et al. 2023

Sensors

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Recording the trajectory of table tennis balls in real-time enables the analysis of the opponent’s attacking characteristics and weaknesses. The current analysis of the ball paths mainly relied on human viewing, which lacked certain theoretical data support. In order to solve the problem of the lack of objective data analysis in the research of table tennis competition, a target detection algorithm-based table tennis trajectory extraction network was proposed to record the trajectory of the table tennis movement in video. The network improved the feature reuse rate in order to achieve a lightweight network and enhance the detection accuracy. The core of the network was the “feature store & return” module, which could store the output of the current network layer and pass the features to the input of the network layer at the next moment to achieve efficient reuse of the features. In this module, the Transformer model was used to secondarily process the features, build the global association information, and enhance the feature richness of the feature map. According to the designed experiments, the detection accuracy of the network was 96.8% for table tennis and 89.1% for target localization. Moreover, the parameter size of the model was only 7.68 MB, and the detection frame rate could reach 634.19 FPS using the hardware for the tests. In summary, the network designed in this paper has the characteristics of both lightweight and high precision in table tennis detection, and the performance of the proposed model significantly outperforms that of the existing models.

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Section: Related Workmentioning

confidence: 99%

Table Tennis Track Detection Based on Temporal Feature Multiplexing Network

Liu

et al. 2023

Sensors

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“…3 It can be seen from the interview and survey that, at present, in a university, ordinary badminton enthusiasts often choose to take a slow walk to relieve exercise fatigue after finishing badminton sports. 4 After breathing evenly, they go back to rest, and rarely carry out special relaxation training. Many college badminton club enthusiasts also only carried out relatively simple relaxation training.…”

Section: Introductionmentioning

confidence: 99%

Relaxation Effects on Fatigue and Physical Fitness in Badminton Athletes

Shubao

Han

2023

Rev Bras Med Esporte

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Introduction: Badminton is characterized by a high amount of exercise and high intensity of work. Muscle pain and discomfort often occur throughout the game, so some relaxation training is necessary. Objective: Study the effect of relaxation training on recovery from sports fatigue and fitness recovery during badminton. Methods: Badminton training was conducted three times a week. The duration of the exercises of the experimental and control group students was the same. The experimental group adopted the relaxation training form, including stretching, aerobic, and other relaxation actions. The duration of relaxation training was 15 minutes, while the control group continued to use the traditional relaxation method. Results: Lactate in the experimental group showed a continuous downward trend, from 2.09 to 1.93 and then to 1.62; heart rate increased from 84.73 to 85.48, then decreased to 81.57, and finally increased to 85.62. The optimization effect was greater than in the control group. In the experimental group, the speed and strength of the athletes improved considerably. Conclusion: Relaxation training can improve athletes’ fatigue, promoting body development and improving strength and speed in physical fitness. Level of evidence II; Therapeutic studies - investigation of treatment outcomes.

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“…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.…”

Section: Introductionmentioning

confidence: 99%

“…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.…”

Section: Introductionmentioning

confidence: 99%

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

Wei

Weng

2023

IET Image Processing

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Court line extraction is one of the important steps in the analysis of sport videos. The court extraction is the foundation of the analysis of badminton video, and an efficient method with horizontal line projection K‐means machine learning algorithm to extract court lines from different broadcast badminton tournament videos is proposed in this paper. The horizontal lines are projected into 1‐D histogram signal; then the signal is trained to learn the intensity of the histogram signal for locating the positions of the horizontal court lines. After the equations of the horizontal court lines and the court lines in the vertical direction have been formulized, the intersection points of the court lines can be calculated and the court line can be extracted. The experimental results show that the proposed method can extract the court lines more efficiently than that done by the Hough transform‐related algorithms, which are widely applied in computer vision and self‐driving car applications.

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Motion recognition technology of badminton players in sports video images

Cited by 22 publications

References 25 publications

Table Tennis Track Detection Based on Temporal Feature Multiplexing Network

Table Tennis Track Detection Based on Temporal Feature Multiplexing Network

Relaxation Effects on Fatigue and Physical Fitness in Badminton Athletes

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

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