Abstract
It is difficult to track the posture of players in the course, mainly because of the changing environment and players. In this paper, the improved neural network is used to extract the trajectory characteristics of the athletes in the football player’s game video, and the network is trained on a large number of data objects containing similarity objects, which improves the ability of the algorithm to distinguish the athlete’s trajectory. A scheme of soccer attitude tracking based on twin neural network. The experimental results show that the algorithm has a good effect in the field of football and the accuracy is over 90% and the Siamese neural network is better than a traditional convolutional neural network.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Journal of Ambient Intelligence and Humanized Computing
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.