Robust traffic event extraction via content understanding for highway surveillance system

A method to extract traffic events by integrating the low-level, middle-level, and high-level feature extraction modules is developed in this research. The low-level module extracts features such as motion, size, and location. The middle-level module builds a bridge between the road surface plane in the real world and the captured image plane via geometric analysis. Finally, the high-level module identifies traffic events such as "traffic jam", "lane change", and "traffic rule violation", which require the understanding of video content in a specific knowledge domain. In the high-level module, various traffic events are related to motion characteristics obtained from the middle-level module. It is demonstrated by experimental results that the proposed system can achieve robust traffic event extraction.