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Traffic Flow Estimation from Road Surveillance

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

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Traffic Flow Estimation from Road Surveillance. / Mehboob, Fozia; Abbas, Muhammad; Almotaeryi, Resheed et al.
2015 IEEE International Symposium on Multimedia (ISM). IEEE, 2015. p. 605-608.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

Harvard

Mehboob, F, Abbas, M, Almotaeryi, R, Jiang, R, Al-Maadeed, S & Bouridane, A 2015, Traffic Flow Estimation from Road Surveillance. in 2015 IEEE International Symposium on Multimedia (ISM). IEEE, pp. 605-608. https://doi.org/10.1109/ism.2015.14

APA

Mehboob, F., Abbas, M., Almotaeryi, R., Jiang, R., Al-Maadeed, S., & Bouridane, A. (2015). Traffic Flow Estimation from Road Surveillance. In 2015 IEEE International Symposium on Multimedia (ISM) (pp. 605-608). IEEE. https://doi.org/10.1109/ism.2015.14

Vancouver

Mehboob F, Abbas M, Almotaeryi R, Jiang R, Al-Maadeed S, Bouridane A. Traffic Flow Estimation from Road Surveillance. In 2015 IEEE International Symposium on Multimedia (ISM). IEEE. 2015. p. 605-608 doi: 10.1109/ism.2015.14

Author

Mehboob, Fozia ; Abbas, Muhammad ; Almotaeryi, Resheed et al. / Traffic Flow Estimation from Road Surveillance. 2015 IEEE International Symposium on Multimedia (ISM). IEEE, 2015. pp. 605-608

Bibtex

@inproceedings{2722963cc7a843ff81c88b0a3dbeedf2,
title = "Traffic Flow Estimation from Road Surveillance",
abstract = "Real-time traffic analysis using the road mounted surveillance cameras present multitude of benefits. This kind of traffic video processing has become an important means for intelligent traffic management and control. The estimation and analysis of road traffic motion is an involved task in computer vision and video processing. In our work, morphological operations and region growing method are used to perform salient motion detection of objects. In classical background extraction method, the background has to be learnt from large numbers of frames. In our method, no a prior knowledge about shape and size of object is acquired. Instead, sum of square difference is estimated via online learning for the calculation of the centroid distance. The test results indicate that the road vehicles and their statistics are determined through our algorithm with complete fidelity.",
author = "Fozia Mehboob and Muhammad Abbas and Resheed Almotaeryi and Richard Jiang and Somaya Al-Maadeed and Ahmed Bouridane",
year = "2015",
doi = "10.1109/ism.2015.14",
language = "English",
isbn = "9781509003792",
pages = "605--608",
booktitle = "2015 IEEE International Symposium on Multimedia (ISM)",
publisher = "IEEE",

}

RIS

TY - GEN

T1 - Traffic Flow Estimation from Road Surveillance

AU - Mehboob, Fozia

AU - Abbas, Muhammad

AU - Almotaeryi, Resheed

AU - Jiang, Richard

AU - Al-Maadeed, Somaya

AU - Bouridane, Ahmed

PY - 2015

Y1 - 2015

N2 - Real-time traffic analysis using the road mounted surveillance cameras present multitude of benefits. This kind of traffic video processing has become an important means for intelligent traffic management and control. The estimation and analysis of road traffic motion is an involved task in computer vision and video processing. In our work, morphological operations and region growing method are used to perform salient motion detection of objects. In classical background extraction method, the background has to be learnt from large numbers of frames. In our method, no a prior knowledge about shape and size of object is acquired. Instead, sum of square difference is estimated via online learning for the calculation of the centroid distance. The test results indicate that the road vehicles and their statistics are determined through our algorithm with complete fidelity.

AB - Real-time traffic analysis using the road mounted surveillance cameras present multitude of benefits. This kind of traffic video processing has become an important means for intelligent traffic management and control. The estimation and analysis of road traffic motion is an involved task in computer vision and video processing. In our work, morphological operations and region growing method are used to perform salient motion detection of objects. In classical background extraction method, the background has to be learnt from large numbers of frames. In our method, no a prior knowledge about shape and size of object is acquired. Instead, sum of square difference is estimated via online learning for the calculation of the centroid distance. The test results indicate that the road vehicles and their statistics are determined through our algorithm with complete fidelity.

U2 - 10.1109/ism.2015.14

DO - 10.1109/ism.2015.14

M3 - Conference contribution/Paper

SN - 9781509003792

SP - 605

EP - 608

BT - 2015 IEEE International Symposium on Multimedia (ISM)

PB - IEEE

ER -