Department of Physical Education, Guangzhou City University of Technology, Guangzhou 510800, Guangdong, China.
College of Physical Education, Guangdong University of Education, Guangzhou 510800, Guangdong, China.
Comput Intell Neurosci. 2022 Jul 31;2022:6951532. doi: 10.1155/2022/6951532. eCollection 2022.
Computer vision is an interesting branch of artificial intelligence which is dedicated to how electronic devices can achieve the level of capabilities to perceive things just like ordinary human beings do. In order to solve the poor effect of video for the detection of target in football matches and the low accuracy of target tracking, this paper aims to make a deep exploration of the methods of video for the detection of target and tracking in football matches. The video moving for the detection of target method based on background model is used to extract the image in the background of the matching video which improves the light flow field. Secondly, the video differential image is acquired according to the difference of colors, the ghost target of the image in the video background model is scientifically determined, the ghost degree of the pixel points of the image is scientifically determined, and the flicker matrix of the target image is constructed. The number of pixels of the moving target is derived. A meanshift-based video target tracking algorithm is used in conjunction for the detection of target result to determine whether to track the target image until the overall video target tracking task is completed, move the central position of the target frame and background frame to the target position, select the best one to adapt to the target change, and determine whether to track the target image until the overall video target tracking task is completed. The simulation results suggest that the approach described in this study is capable of detecting and tracking moving objects, as well as improving target recognition and tracking accuracy.
计算机视觉是人工智能的一个有趣分支，致力于研究电子设备如何达到像普通人一样感知事物的能力。为了解决足球比赛中目标视频检测效果差和目标跟踪精度低的问题，本文旨在深入探索足球比赛中目标视频检测和跟踪的方法。使用基于背景模型的视频目标运动检测方法来提取匹配视频的背景图像，提高光流场。其次，根据颜色差异获取视频差分图像，科学确定视频背景模型中图像的鬼影目标，科学确定图像像素点的鬼影程度，构建目标图像的闪烁矩阵。得出运动目标的像素数。结合基于meanshift 的视频目标跟踪算法对检测到的目标结果进行判断，是否跟踪目标图像，直到完成整个视频目标跟踪任务，将目标帧和背景帧的中心位置移动到目标位置，选择最适合目标变化的位置，是否跟踪目标图像，直到完成整个视频目标跟踪任务。仿真结果表明，本研究提出的方法能够检测和跟踪运动目标，提高目标识别和跟踪精度。
