scholarly journals Study on the Automatic Basketball Shooting System Based on the Background Subtraction Method

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yan Hu ◽  
Yong Xu

There are many drawbacks such as clustering, background updating, inaccurate testing results, and low anti-interference performance in traditional moving target detection theory. In our study, a background subtraction method to automatically capture the basketball shooting trajectory was used to eliminate the drawbacks of the fixed-point shooting system such as cumbersome installation and time and manpower consumption. It also can improve the accuracy and efficiency of moving target detection. We also synthetically compared to common methods including the optical flow method and interframe difference method. Results showed that the background subtraction method has better accuracy with an accuracy rate over about 90% than the interframe subtraction method (88%) and the optimal flow method (85%) and presents excellent robustness with considering variable speed and nonrigid objects. Meanwhile, the automatic detection system for basketball shooting based on background subtraction is built by coupling background subtraction with detection characteristics. The system detection speed built is further accelerated, and the image denoising is improved. The trajectory error rate is about 0.3, 0.4, and 0.5 for the background subtraction method, interframe subtraction method, and optimal flow method, respectively.

2020 ◽  
Vol 39 (6) ◽  
pp. 8953-8960
Author(s):  
Jin Wang

Facing COVID-19 epidemic, many countries have recently strengthened epidemic prevention and control measures. The reliability of safety management is of great significance to personnel management and control during the COVID-19 epidemic period. The focus of security management of early warning is to monitor and identify the moving target. The current optical flow method is vulnerable to the influence of light changes and background movement, and it is not very accurate for moving target detection in dynamic complex background. In this paper, aiming at the traditional Lucas Kanade optical flow method, the inter frame difference method, mean shift clustering algorithm and morphological processing are combined to optimize and improve on the original basis, so that the moving target detection effect in both simple and complex environments is significantly improved. At the same time, the improved algorithm also reduces the execution time to a certain extent, and has a certain resistance to noise interference such as light changes. This has a certain ability test value for personnel control during the epidemic.


IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 152612-152623 ◽  
Author(s):  
Junhui Zuo ◽  
Zhenhong Jia ◽  
Jie Yang ◽  
Nikola Kasabov

2018 ◽  
Vol 10 (5) ◽  
pp. 742 ◽  
Author(s):  
Wenjie Shen ◽  
Yun Lin ◽  
Lingjuan Yu ◽  
Feiteng Xue ◽  
Wen Hong

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