Frontiers in Sport Research, 2022, 4(5); doi: 10.25236/FSR.2022.040507.
Wanyue Li, Jie Cui
School of Economics and Management, Shanghai University of Sports, Shanghai, China
In order to explore the effect of convolutional neural network (CNN) on the detection of athletes and balls in table tennis, and to solve the problems of low accuracy and weak generalization ability of table tennis athletes training data, this paper analyzed videos of table tennis athletes. For the detection of multiple targets in the videos, including athletes and balls, we used Yolov3 as a deep learning framework, and CNN as an automatic detection method when processing images. We trained and test the video data to improve the stability and accuracy of target detection, through modifying its model on the basis of the Yolov3 model. Finally, we detect the movement trajectories of athletes and balls in table tennis videos stably, and the accuracy is above 0.8.
Convolutional Neural Network; Yolov3 Model; Table Tennis; Multi-Target Detection
Wanyue Li, Jie Cui. Multi-Target Detection of Table Tennis Video Based on CNN and Yolov3. Frontiers in Sport Research (2022) Vol. 4, Issue 5: 24-28. https://doi.org/10.25236/FSR.2022.040507.
 Shang Zhiliang, Wang Wei, Yang Mingzhen, Jia Mingzhen, Ma Cunliang. Garbage image processing and improvement based on convolutional neural network [J]. Internet of Things Technologies, 2022,12(08):93-96+99.
 Hou Maoze, Ma Yanqiong, Tian Senlin, Ouyang Hao, Zhao Heng, Li Yingjie, Tie Cheng, Zhao Qilin. Research on water pollution traceability based on convolutional neural network identification of three-dimensional fluorescence spectrum[J/OL].Environmental Monitoring in China:1-8[2022-08-26].
 Lu Fan. Research on human pose estimation based on deep convolutional neural networks[D]. Southwest Jiaotong University, 2021.
 Zhou Yifeng, Yang Binfeng.A palyer detection method using convolution nerual network in sports videos[J].Journal of Xiangtan University(Natural Science Edition),2017,39(01):95-98.
 Ouyang Ruiqi, Yong Yang, Wang Bingxue.Application of convolution neural network in aircraft type recognition[J].Ordnance Industry Automation, 2017,36(12):71-75.
 Yang Lanlan, Gao Mingyu, Wang Chenning, Feng Dongjie, Lv Xinrui. Research on facial expression recognition based on data enhancement[J].Computer Products and Circulation, 2020(11):128-129.
 Video source website. https://lab.osai.ai/datasets/openttgames/.
 Cao Xiaoming, Zhang Yonghe, Pan Meng , Zhu Shan, Yan Hailiang. Research on student engagement recognition method from the perspective of artificial intelligence: analysis of deep learning experiment based on a multimodal data fusion[J].Journal of Distance Education, 2019,37(01):32-44.