Event analysis based on multiple video sensors for cooperative environment perception

Safety is considered as one of the most crucial aspects in the modern transportation domain. In this paper, we benefit from the videos captured by multiple external video sensors from infrastructure, and propose an algorithm to perceive the environment via these data from different aspects. The algorithm consists of two parts: the descriptor for representing the event and the classification method for analyzing the scenes. The covariance matrix feature descriptor is proposed to fuse the optical flow and the intensity of the image, and the nonlinear one-class SVM with a multi-kernel strategy is used to detect the unusual events in the scene. The method is applied to analyze events in the video surveillance dataset with promising results obtained.