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.