Vision-based vehicle event detection through visual rhythm analysis

In this paper, a simple and reliable on-road vehicle event detection algorithm is proposed to identify events for vehicle. A virtual line at the same position of a frame is employed to extract visual rhythm. The visual rhythm is a compact representation of a video that captures the temporal information of vehicle status of a coarsely spatially sampled video sequence. By analyzing statistical characteristics of the visual rhythm, the events such as safe distance, passing and lane changing can be effectively detected. The proposed techniques can prevent accidents and improve traffic safety by monitoring the alertness of drivers, augmenting vision fields to prevent collision. The proposed system is efficient both in terms of computational complexity and memory requirements. Experimental results show the efficiency and effectiveness of the proposed system for intelligent transport system.