基于帧间差分和统计直方图的交通视频背景建模方法

Method for Traffic Video Background Modeling Based on Inter-frame Difference and Statistical Histogram

针对城市道路交通视频难以直接提取交通背景,导致前景目标检测不准确的问题,提出了一种基于帧间差分和统计直方图的交通视频背景建模方法。一个好的背景建模方法有利于后续目标检测及跟踪任务的良好开展。所提方法首先利用帧间差分法提取视频中每帧的大致运动区域作为前景运动目标,再利用统计直方图获得图像的灰度值分布状态,进行背景图像的估计,从而提取出高整洁度、低噪声点的背景图像。与已有背景建模方法的对比实验结果表明,无论是在普通交通场景,还是在车辆行驶缓慢的典型交通场景中,所提方法都可以提取出与真实背景相似匹配度更高的背景图像。

Aiming at the problem of inaccurate foreground object detection caused by the difficulty of extracting traffic background directly from urban road traffic video,a method for traffic video background modeling based on the combination of inter-frame difference and statistical histogram is proposed.A good background modeling method is conducive to the smooth development of subsequent object detecting and tracking tasks.Firstly,it uses inter-frame difference method to extract the approximate motion region of each frame in the video as the foreground moving object.Then,it uses statistical histogram to obtain the gray value distribution state of the image and estimates the background image,thereby a background image with high cleanliness and low noise points is extracted.Compared with the existing background modeling method,the experimental results show that the proposed method can extract the background image with higher matching degree with the real background,both in the ordinary traffic scenes and the typical traffic scene where vehicles are moving slowly.