An abandoned object detection system based on dual background segmentation

Singh, A. K. and Sawan, S. and Hanmandlu, M. and Madasu, V. K. and Lovell, B. C. (2009) An abandoned object detection system based on dual background segmentation. In: Advanced Video and Signal Based Surveillance, 2009. AVSS '09. Sixth IEEE International Conference on, 2 - 4 September, Genova, Italy.

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Abstract

An abandoned object detection system is presented and evaluated using benchmark datasets. The detection is based on a simple mathematical model and works efficiently at QVGA resolution at which most CCTV cameras operate. The pre-processing involves a dual-time background subtraction algorithm which dynamically updates two sets of background, one after a very short interval (less than half a second) and the other after a relatively longer duration. The framework of the proposed algorithm is based on the Approximate Median model. An algorithm for tracking of abandoned objects even under occlusion is also proposed. Results show that the system is robust to variations in lighting conditions and the number of people in the scene. In addition, the system is simple and computationally less intensive as it avoids the use of expensive filters while achieving better detection results.

Keywords:Object detection, Cameras, Layout, Video surveillance, Mathematical model, Subtraction techniques, Data mining, Image converters, Image segmentation, Matrix converters, approximation theory, closed circuit television, image resolution, video cameras, tracking, left baggage detection, background segmentation
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Engineering
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ID Code:28760
Deposited On:02 Oct 2017 13:24

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