Abandoned object detection in highway scene

Abandoned object detection in highway scene is one of the most crucial tasks in intelligent visual surveillance systems. However, few previous methods on abandoned object detection have focused on this important problem. In this paper, we present a new framework to detect the abandoned objects. In our framework, Gaussian mixture model (GMM) is used to model the background, but it is not updated every frame for keeping the abandoned objects in the foreground. To erase the noise caused by sunshine or wind, we bring an edge statistics feature based approach into the framework. Moreover, object tracking module is also integrated into the framework for a better abandoned object detection. Extensive experiments are conducted. The experimental results demonstrate that our proposed framework is not only real-time enough for practical application, but also have a very high detection accuracy.