Detection model of abnormal behavior based on DOG
Bai Hui-xiao · Jisuanji gongcheng yu sheji · 2008
In order to identify pedestrian movement in monitoring system,an abnormal behavior analysis module of the system is presented,using real-time unsupervised.It called dynamic oriented graph(DOG) is used to predict and detect abnormal behaviors.The DOG method characterizes observed actions by a structure of unidirectional connected nodes,each one node defining a region in the hyperspace of attributes measured from the observed moving objects and having assigned a probability to generate an abnormal behavior.Experimental result show that the DOG method can track successfully moving objects,and it is robust and accurate.