Affiliation:
1. Graduate School, Namseoul University, Cheonan, Republic of Korea
2. Department of Sports Art, Hebei Institute of Physical Education, Hebei, China
Abstract
In order to improve the real-time detection effect, therefore, a research on real-time scene detection of sports dance competition based on deep learning is proposed. The collected scene image is grayed by using the weighted average method, and the best image interpolation is calculated by using the deep learning method, so as to realize the smooth processing of sawtooth and mosaic information generated by panoramic mapping. After selecting the cube model, the processed scene information is projected to the visual plane to construct the panorama of the competition scene. Finally, combined with the three-frame difference, the changes between adjacent image frames are calculated to obtain the moving target. The test results show that the motion detection accuracy of professional dancers can reach more than 75.0% and that of amateur dancer can reach more than 64.2%.
Subject
Electrical and Electronic Engineering,Computer Networks and Communications,Information Systems