Event detection for intelligent car park video surveillance

Authors:
Georgios Diamantopoulos;Michael Spann
Affiliations:
Department of Electrical, Electronic and Computer Engineering, University of Birmingham, Birmingham B15 2TT, UK;Department of Electrical, Electronic and Computer Engineering, University of Birmingham, Birmingham B15 2TT, UK
Venue:
Real-Time Imaging
Year:
2005

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Abstract

Intelligent surveillance has become an important research issue due to the high cost and low efficiency of human supervisors, and machine intelligence is required to provide a solution for automated event detection. In this paper we describe a real-time system that has been used for detecting tailgating, an example of complex interactions and activities within a vehicle parking scenario, using an adaptive background learning algorithm and intelligence to overcome the problems of object masking, separation and occlusion. We also show how a generalized framework may be developed for the detection of other complex events.