An abandoned object detection system based on dual background segmentation

Singh, A., Sawan, S., Hanmandlu, M., Madasu, V. K. and Lovell, B. C. (2009). An abandoned object detection system based on dual background segmentation. In: Lisa O’Conner, Proceedings Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance. AVSS 2009: 6th IEEE International Conference on Advanced Video and Signal Based Surveillance, Genoa, Italy, (352-357). 2-4 September 2009.


Author Singh, A.
Sawan, S.
Hanmandlu, M.
Madasu, V. K.
Lovell, B. C.
Title of paper An abandoned object detection system based on dual background segmentation
Conference Paper Type Fully Published Paper
Conference name AVSS 2009: 6th IEEE International Conference on Advanced Video and Signal Based Surveillance    (ERA 2010 Rank B)
DOI 10.1109/AVSS.2009.74
Conference location Genoa, Italy
Conference dates 2-4 September 2009
Convener IEEE Computer Society; IEEE Signal Processing Society
Proceedings title Proceedings Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Journal name Avss: 2009 6th Ieee International Conference On Advanced Video and Signal Based Surveillance
Editor Lisa O’Conner
Place published Los Alamitos, CA, U.S.A.
Publisher Institute of Electrical and Electronics Engineers (IEEE)
Publication date 2009
ISBN 9781424447558; 1424447550; 9780769537184; 0769537189
Start page 352
End page 357
Total pages 6
Language eng
Formatted Abstract/Summary 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.
© 2009 IEEE.
Keyword Video surveillance
Left baggage detection
Background segmentation
Tracking
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ
Additional Notes Author title: "An abandoned object detection system using dual background segmentation".

 
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