A football training method based on improved tiny-yolov3 and virtual reality

The traditional way of football training could be subject to some factors such as the field, and the problems and scenes in the training can not be recovered fully. Thus, this paper proposes a football training method based on the improved tiny-yolovs3 model and the virtual reality (VR). Firstly, th...

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Bibliographic Details
Published inMultimedia tools and applications Vol. 81; no. 10; pp. 14283 - 14301
Main Authors Xiao, Dong, Niu, Jinbo, Feng, Jian
Format Journal Article
LanguageEnglish
Published New York Springer US 01.04.2022
Springer Nature B.V
Subjects
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Football
Multimedia Information Systems
Special Purpose and Application-Based Systems
Training
Virtual reality
Densenet
Tiny-yolov3
Football training
Convolutional neural network
Target detection
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Summary:The traditional way of football training could be subject to some factors such as the field, and the problems and scenes in the training can not be recovered fully. Thus, this paper proposes a football training method based on the improved tiny-yolovs3 model and the virtual reality (VR). Firstly, the paper makes use of the improved tiny-yolov3 model to detect the football in motion. Then, the paper uses the binocular camera to get the coordinates of the football. Finally, the paper reproduces the position of football in the virtual reality environment. The experimental results show that the football training method is feasible.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1380-7501
1573-7721
DOI:10.1007/s11042-022-12404-2