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Computer vision based traffic monitoring system for multi-track freeways

Journal Article


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Abstract


  • Nowadays, development is synonymous with construction of infrastructure. Such road infrastructure needs constant attention in terms of traffic monitoring as even a single disaster on a major artery will disrupt the way of life. Humans cannot be expected to monitor these massive infrastructures over 24/7 and computer vision is increasingly being used to develop automated strategies to notify the human observers of any impending slowdowns and traffic bottlenecks. However, due to extreme costs associated with the current state of the art computer vision based networked monitoring systems, innovative computer vision based systems can be developed which are standalone and efficient in analyzing the traffic flow and tracking vehicles for speed detection. In this article, a traffic monitoring system is suggested that counts vehicles and tracks their speeds in realtime for multi-track freeways in Australia. Proposed algorithm uses Gaussian mixture model for detection of foreground and is capable of tracking the vehicle trajectory and extracts the useful traffic information for vehicle counting. This stationary surveillance system uses a fixed position overhead camera to monitor traffic.

Publication Date


  • 2014

Citation


  • Z. Iftikhar, P. Premaratne & P. Vial, "Computer vision based traffic monitoring system for multi-track freeways," Lecture Notes in Computer Science, vol. 8589, pp. 339-349, 2014.

Scopus Eid


  • 2-s2.0-84958522983

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=3921&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/2912

Number Of Pages


  • 10

Start Page


  • 339

End Page


  • 349

Volume


  • 8589

Abstract


  • Nowadays, development is synonymous with construction of infrastructure. Such road infrastructure needs constant attention in terms of traffic monitoring as even a single disaster on a major artery will disrupt the way of life. Humans cannot be expected to monitor these massive infrastructures over 24/7 and computer vision is increasingly being used to develop automated strategies to notify the human observers of any impending slowdowns and traffic bottlenecks. However, due to extreme costs associated with the current state of the art computer vision based networked monitoring systems, innovative computer vision based systems can be developed which are standalone and efficient in analyzing the traffic flow and tracking vehicles for speed detection. In this article, a traffic monitoring system is suggested that counts vehicles and tracks their speeds in realtime for multi-track freeways in Australia. Proposed algorithm uses Gaussian mixture model for detection of foreground and is capable of tracking the vehicle trajectory and extracts the useful traffic information for vehicle counting. This stationary surveillance system uses a fixed position overhead camera to monitor traffic.

Publication Date


  • 2014

Citation


  • Z. Iftikhar, P. Premaratne & P. Vial, "Computer vision based traffic monitoring system for multi-track freeways," Lecture Notes in Computer Science, vol. 8589, pp. 339-349, 2014.

Scopus Eid


  • 2-s2.0-84958522983

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=3921&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/2912

Number Of Pages


  • 10

Start Page


  • 339

End Page


  • 349

Volume


  • 8589