Detection of Anomalies in Traffic Scene Surveillance

Detecting anomalies in the Traffic Systems could be very useful for the analysis of traffic rule violation, fault detection and other traffic-related issues. In this paper trajectory-based anomaly detection using spatial temporal analysis, K-means, linear regression, z score and Hierarchical temporal memory clustering algorithm are analyzed. The spatial localization of an object is considered as an event. Traffic anomaly detection rules are formulated in three levels: Point anomaly, Sequential anomaly and Co-occurrence anomaly. This paper analyses the performance of various traffic anomaly detection methodologies in terms of accuracy to reduce false alarm.