Adaptive background updating and shadow detection in traffic scenes
交通场景中车辆的运动检测与阴影消除

In this paper, we present a real-time background modeling framework for moving vehicle segmentation in traffic surveillance scenes. First, we propose a new adaptive background modeling method called Balloon Model established in the color space, which fixes the error of non-moving objects in the parameter models; second, an effective shadow detection approach is developed to detect shadows in traffic scenes, which adopts feature fusion method to achieve the segmentation of vehicles. Compared to the other methods, this technique achieves a higher accuracy and is faster.