Sensor Fusion Basketball Shooting Posture Recognition System Based on CNN

Fan, Jingjin; Wang, Guojie; Zhang, Li; Sun, Shilei

doi:10.1155/2021/6664776

Cited by 24 publications

(12 citation statements)

References 31 publications

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“…Among them, A and B are system parameters and H represents the observation system parameters [35,36].…”

Section: Kcf Tracking Algorithm Fused With Kalman Predictionmentioning

confidence: 99%

[Retracted] Research on Recognition Method of Basketball Goals Based on Image Analysis of Computer Vision

Zhang¹

2021

Journal of Sensors

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Moving target detection is involved in many engineering applications, but basketball has some difficulties because of the time-varying speed and uncertain path. The purpose of this paper is to use computer vision image analysis to identify the path and speed of a basketball goal, so as to meet the needs of recognition and achieve trajectory prediction. This research mainly discusses the basketball goal recognition method based on computer vision. In the research process, Kalman filter is used to improve the KCF tracking algorithm to track the basketball path. The algorithm of this research is based on MATLAB, so it can avoid the mixed programming of MATLAB and other languages and reduce the difficulty of interface design software. In the aspect of data acquisition, the extended EPROM is used to store user programs, and parallel interface chips (such as 8255A) can be configured in the system to output switch control signals and display and print operations. The automatic basketball bowling counter based on 8031 microprocessor is used as the host computer. After the level conversion by MAX232, it is connected with the RS232C serial port of PC, and the collected data is sent to the workstation recording the results. In order to consider the convenience of user operation, the GUI design of MATLAB is used to facilitate the exchange of information between users and computers so that users can see the competition results intuitively. The processing frame rate of the tested video image can reach 60 frames/second, more than 25 frames/second, which meet the real-time requirements of the system. The results show that the basketball goal recognition method used in this study has strong anti-interference ability and stable performance.

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“…Among them, A and B are system parameters and H represents the observation system parameters [35,36].…”

Section: Kcf Tracking Algorithm Fused With Kalman Predictionmentioning

confidence: 99%

[Retracted] Research on Recognition Method of Basketball Goals Based on Image Analysis of Computer Vision

Zhang¹

2021

Journal of Sensors

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“…In order to win the game, players must have the ability to shoot accurately. Studies show that the most important factor in winning the game and establishing superiority is the ability to shoot accurately 11,14,21 .…”

Section: Discussionmentioning

confidence: 99%

“…In basketball, it is important for the players playing in each position to show high performance in order to win the match. Studies show that the most important factor over victory is the accurate shooting 11,14,21 .…”

Section: Introductionmentioning

confidence: 99%

The Comparison of Selected Physical and Physiological Parameters of Elite Basketball Players According to their Playing Positions

Erol¹,

Karahançer²,

Özden³

et al. 2021

PJMHS

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Background: This research was conducted to compare the physical and physiological parameters of elite basketball players according to their playing positions and to contribute to the literature. Methods: Eighteen elite basketball players who regularly train and compete in the national team participated in the research voluntarily. Participants were grouped as guard, forward and center according to the pitch positions. Vertical jump and sprint tests were used to evaluate the anaerobic performance of the participants. The Yo-Yo intermittent recovery test was applied to evaluate the aerobic performances. In addition, hemogram analyzes of the blood samples of the participants were made and hematocrit and hemoglobin parameters related to aerobic performance were examined. Kruskal Wallis-H and Mann Whitney U tests were used for statistical analyses. Results: The analyzes show that the guards had higher vertical jump, yo-yo and VO2max averages compared to the centers, and a significantly lower 30 m running average. It was determined that the forward players had higher anaerobic power than the guards, and yo-yo running and VO2max averages were significantly higher than the center players. Conclusion: In conclusion, it is thought that the difference between guard, forward and center players who voluntarily participated in the study is due to the physical characteristics of the basketball players and the different training programs applied to the players playing in different positions. Keywords: Basketball Player, Playing Position, Physical Characteristics, Physiological Characteristics

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“…J. Fan et al [39] have designed a sensor fusion basketball shooting posture recognition system based on convolutional neural networks. It has collected 12,177 sensor fusion basketball shooting posture data entries of 13 Chinese adult male subjects aged 18-40 years and with at least 2 years of basketball experience without professional training.…”

Section: Wearable Sensingmentioning

confidence: 99%