An abandoned object detection system based on dual background segmentation
An abandoned object detection system based on dual background segmentation
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.
Background segmentation, Left baggage detection, Tracking, Video surveillance
352-357
Singh, A.K.
6df7029f-21e3-4a06-b5f7-da46f35fc8d3
Sawan, S.
8699ac13-4c9f-46f7-8912-d9029cf8abc5
Hanmandlu, M.
db16ae19-479e-4a67-8d9a-be77e09c049e
Madasu, V. K.
facdb790-2e00-4c2e-a73b-f8e63ea40046
Lovell, B. C.
47ef4b17-cd96-4688-a44f-88fbe8c0cb2a
25 December 2009
Singh, A.K.
6df7029f-21e3-4a06-b5f7-da46f35fc8d3
Sawan, S.
8699ac13-4c9f-46f7-8912-d9029cf8abc5
Hanmandlu, M.
db16ae19-479e-4a67-8d9a-be77e09c049e
Madasu, V. K.
facdb790-2e00-4c2e-a73b-f8e63ea40046
Lovell, B. C.
47ef4b17-cd96-4688-a44f-88fbe8c0cb2a
Singh, A.K., Sawan, S., Hanmandlu, M., Madasu, V. K. and Lovell, B. C.
(2009)
An abandoned object detection system based on dual background segmentation.
In 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance.
IEEE.
.
(doi:10.1109/AVSS.2009.74).
Record type:
Conference or Workshop Item
(Paper)
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.
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More information
Published date: 25 December 2009
Venue - Dates:
6th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2009, , Genova, Italy, 2009-09-02 - 2009-09-04
Keywords:
Background segmentation, Left baggage detection, Tracking, Video surveillance
Identifiers
Local EPrints ID: 430882
URI: http://eprints.soton.ac.uk/id/eprint/430882
PURE UUID: 9b3ffb83-6e84-494b-a2d3-151bd912a8ce
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Date deposited: 16 May 2019 16:30
Last modified: 16 Mar 2024 04:40
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Contributors
Author:
A.K. Singh
Author:
S. Sawan
Author:
M. Hanmandlu
Author:
V. K. Madasu
Author:
B. C. Lovell
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