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Non-overlapping multi-camera detection and tracking of vehicles in tunnel surveillance

Jorge Niño Castañeda UGent, Vedran Jelača UGent, Andres Frias Velazquez UGent, Aleksandra Pizurica UGent, Wilfried Philips UGent, Reyes Rios Cabrera and Tinne Tuytelaars (2011) Digital Image Computing Techniques and Applications, International conference, Proceedings. p.591-596
abstract
We propose a real-time multi-camera tracking approach to follow vehicles in a tunnel surveillance environment with multiple non-overlapping cameras. In such system, vehicles have to be tracked in each camera and passed correctly from one camera to another through the tunnel. This task becomes extremely difficult when intra-camera errors are accumulated. Most typical issues to solve in tunnel scenes are due to low image quality, poor illumination and lighting from the vehicles. Vehicle detection is performed using Adaboost detector, speeded up by separating different cascades for cars and trucks improving general accuracy of detection. A Kalman Filter with two observations, given by the vehicle detector and an averaged optical flow vector, is used for single-camera tracking. Information from collected tracks is used for feeding the inter-camera matching algorithm, which measures the correlation of Radon transform-like projections between the vehicle images. Our main contribution is a novel method to reduce the false positive rate induced by the detection stage. We impose recall over precision in the detection correctness, and identify false positives patterns which are then included subsequently in a high-level decision making step. Results are presented for the case of 3 cameras placed consecutively in an inter-city tunnel. We demonstrate the increased tracking performance of our method compared to existing Bayesian filtering techniques for vehicle tracking in tunnel surveillance.
Please use this url to cite or link to this publication:
author
organization
year
type
conference
publication status
published
subject
keyword
multi-camera tracking, non-overlapping cameras, tunnel surveillance, vehicle tracking
in
Digital Image Computing Techniques and Applications, International conference, Proceedings
pages
591 - 596
publisher
IEEE
place of publication
Piscataway, NJ, USA
conference name
2011 International conference on Digital Image Computing Techniques and Applications (DICTA 2011)
conference location
Noosa, Australia
conference start
2011-12-06
conference end
2011-12-08
ISBN
9781457720062
DOI
10.1109/DICTA.2011.105
project
VICATS
language
English
UGent publication?
yes
classification
C1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1993468
handle
http://hdl.handle.net/1854/LU-1993468
date created
2012-01-18 15:46:33
date last changed
2012-11-13 16:35:28
@inproceedings{1993468,
  abstract     = {We propose a real-time multi-camera tracking approach to follow vehicles in a tunnel surveillance environment with multiple non-overlapping cameras. In such system, vehicles have to be tracked in each camera and passed correctly from one camera to another through the tunnel. This task becomes extremely difficult when intra-camera errors are accumulated. Most typical issues to solve in tunnel scenes are due to low image quality, poor illumination and lighting from the vehicles. Vehicle detection is performed using Adaboost detector, speeded up by separating different cascades for cars and trucks improving general accuracy of detection. A Kalman Filter with two observations, given by the vehicle detector and an averaged optical flow vector, is used for single-camera tracking. Information from collected tracks is used for feeding the inter-camera matching algorithm, which measures the correlation of Radon transform-like projections between the vehicle images. Our main contribution is a novel method to reduce the false positive rate induced by the detection stage. We impose recall over precision in the detection correctness, and identify false positives patterns which are then included subsequently in a high-level decision making step. Results are presented for the case of 3 cameras placed consecutively in an inter-city tunnel. We demonstrate the increased tracking performance of our method compared to existing Bayesian filtering techniques for vehicle tracking in tunnel surveillance.},
  author       = {Ni{\~n}o Casta{\~n}eda, Jorge and Jela\v{c}a, Vedran and Frias Velazquez, Andres and Pizurica, Aleksandra and Philips, Wilfried and Rios Cabrera, Reyes and Tuytelaars, Tinne},
  booktitle    = {Digital Image Computing Techniques and Applications, International conference, Proceedings},
  isbn         = {9781457720062},
  keyword      = {multi-camera tracking,non-overlapping cameras,tunnel surveillance,vehicle tracking},
  language     = {eng},
  location     = {Noosa, Australia},
  pages        = {591--596},
  publisher    = {IEEE},
  title        = {Non-overlapping multi-camera detection and tracking of vehicles in tunnel surveillance},
  url          = {http://dx.doi.org/10.1109/DICTA.2011.105},
  year         = {2011},
}

Chicago
Niño Castañeda, Jorge, Vedran Jelaca, Andres Frias Velazquez, Aleksandra Pizurica, Wilfried Philips, Reyes Rios Cabrera, and Tinne Tuytelaars. 2011. “Non-overlapping Multi-camera Detection and Tracking of Vehicles in Tunnel Surveillance.” In Digital Image Computing Techniques and Applications, International Conference, Proceedings, 591–596. Piscataway, NJ, USA: IEEE.
APA
Niño Castañeda, J., Jelaca, V., Frias Velazquez, A., Pizurica, A., Philips, W., Rios Cabrera, R., & Tuytelaars, T. (2011). Non-overlapping multi-camera detection and tracking of vehicles in tunnel surveillance. Digital Image Computing Techniques and Applications, International conference, Proceedings (pp. 591–596). Presented at the 2011 International conference on Digital Image Computing Techniques and Applications (DICTA 2011), Piscataway, NJ, USA: IEEE.
Vancouver
1.
Niño Castañeda J, Jelaca V, Frias Velazquez A, Pizurica A, Philips W, Rios Cabrera R, et al. Non-overlapping multi-camera detection and tracking of vehicles in tunnel surveillance. Digital Image Computing Techniques and Applications, International conference, Proceedings. Piscataway, NJ, USA: IEEE; 2011. p. 591–6.
MLA
Niño Castañeda, Jorge, Vedran Jelaca, Andres Frias Velazquez, et al. “Non-overlapping Multi-camera Detection and Tracking of Vehicles in Tunnel Surveillance.” Digital Image Computing Techniques and Applications, International Conference, Proceedings. Piscataway, NJ, USA: IEEE, 2011. 591–596. Print.