足球比赛视频中的目标检测与跟踪算法研究

Grey Neural Network Model for Prediction of Carbon Emissions

为在足球视频中有效的检测与跟踪运动目标,需要对足球比赛视频中目标检测与跟踪算法进行研究;当前采用的算法,在动态场景中,存在运动目标检测与跟踪效果不佳的问题;为此,提出一种基于OpenCV的足球比赛视频中目标检测与跟踪算法;该算法结合平均背景算法将足球比赛视频中目标图像分割为前景区与背景区,计算足球比赛视频每一帧目标图像和背景图像之间差值的绝对差值,同时计算每一个目标图像中像素点的平均值与标准值来建立目标图像背景统计模型,利用TMHI算法对足球比赛视频中目标初始图像进行阈值分割,得到初始分割图像,对分割图像进行中值滤波和闭运算,再使用卡尔曼滤波对分割后的目标图像进行处理,得到镜头中目标的质心位置和目标外界矩形框,然后对足球比赛视频中目标进行跟踪;实验证明,该算法有效的检测与跟踪足球视频中运动目标。

In order to target motion detection and tracking effectively in the soccer video, need to study object in soccer video detection and tracking algorithm. The algorithm in dynamic scenes, are moving target detection and tracking problems. Therefore, this paper proposed an algorithm for detection and tracking of target OpenCV in soccer video based on this algorithm. Combining the average background algo rithm will target image segmentation for soccer video in the foreground area and background area, calculates the difference between the abso lute difference of soccer video each frame of target image and background image, and calculate the average value of each pixel in the target im age and the standard value. The establishment of the target image background statistical model, the initial target of soccer video image seg mentation using TMH1 algorithm to obtain the initial image segmentation, median filtering and closed operation of image segmentation, and then use the Calman filter to process the target image after segmentation, target centroid position and get outside rectangular shots target in the frame. Then the goal in soccer video tracking. The experimental results show that the moving target detection and tracking algorithm [or soccer video effectively.