Title :
Abnormal event detection in traffic video surveillance based on local features
Author :
Cui, Lili ; Li, Kehuang ; Chen, Jiapin ; Li, Zhenbo
Author_Institution :
Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
In this article, we proposed an abnormal event detection method based on local features for traffic video surveillance. Firstly, foreground assumed to be moving is detected and affined with morphological operations. Then each foreground region´s area, shape factors (ellipse eccentricity, width-height radio of outside rectangular, and etc.), and pixel moving velocity vector are extracted. Based on those features, regions are classified into different groups as pedestrian, vehicle or noise region, and their behavior is classified using trained local features´ distribution map (location distribution and velocity distribution). Finally, a simple classifier is used to determine objects´ states of normal or abnormal. With the rapid development of ITS (Intelligent Traffic Surveillance), our low complexity and low level abnormality detection method is well fit in early alarm of distributed surveillance system. We have some experiment to show the benefits of proposed method.
Keywords :
automated highways; object detection; video surveillance; abnormal event detection method; foreground region area; intelligent traffic surveillance; local features distribution map; location distribution; morphological operations; pixel moving velocity vector; shape factors; traffic video surveillance; velocity distribution; Event detection; Feature extraction; Noise; Optical reflection; Surveillance; Traffic control; Vehicles; Optical flow; abnormal event detection; local features extraction; video surveillance;
Conference_Titel :
Image and Signal Processing (CISP), 2011 4th International Congress on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-9304-3
DOI :
10.1109/CISP.2011.6099933