Semantic description and traffic event detection modeling for surveillance video

Focusing on retrieving abnormal events from traffic surveillance video databases, a novel video description scheme (DS) is proposed in this work, which divides the object description into moving object description and still region description. Additionally, to address the challenge posed by redundant description data, we developed one group of second order spatial relationship (SR) semantics to represent the changes of SR over time directly; Incorporated with the proposed DS, a semantic model based on description data is developed to implement the low-complexity traffic event detection. Experimental results have shown that the proposed detection model is very efficient.