Design of a hybrid object detection scheme for video sequences

Authors:
Nikolaos Markopoulos;Michalis Zervakis
Affiliations:
Department of Electronic and Computer Engineering, Technical University of Crete, Chania, Greece;Department of Electronic and Computer Engineering, Technical University of Crete, Chania, Greece
Venue:
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
Year:
2005

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Abstract

A method is presented for extracting object information from an image sequence taken by a static monocular camera. The method was developed towards a low computational complexity in order to be used in real-time surveillance applications. Our approach makes use of both intensity and edge information of each frame and works efficiently in an indoor environment. It consists of two major parts: background processing and foreground extraction. The background estimation and updating makes the object detection robust to environment changes like illumination changes and camera jitter. The fusion of intensity and edge information allows a more precise estimation of the position of the different foreground objects in a video sequence. The result obtained are quite reliable, under a variety of environmental conditions.