The invention provides a double-perspective learning-based mountainous area highway vehicle event detection method used for intelligent traffic monitoring. According to the double-perspective learning-based mountainous area highway vehicle event detection method, based on two mutually-independent perspectives, namely, moving object spatial-temporal trajectory mode learning and epipolar plane map-based vehicle moving state analysis, respective independent behaviors of vehicles and overall characteristics of traffic section vehicle flow are detected; the two kinds of characteristics are utilized to detect events such as traffic accidents, traffic congestion, vehicle retrograde travelling and illegal parking; decision level fusion judgment is carried out through correlation processing; a joint inference result can be obtained; and therefore, robustness detection of mountainous area highway vehicle events under a double-perspective fusion framework can be completed. As indicated by experiment results, the detection method has the advantages of low complexity, high real-time performance and excellent performance in terms of a variety of traffic events.
Double-perspective learning-based mountainous area highway vehicle event detection method