Vehicle Velocity Estimation for Traffic Surveillance System
This paper describes an algorithm to estimate realtime vehicle velocity using image processing technique from the known camera calibration parameters. The presented algorithm involves several main steps. First, the moving object is extracted by utilizing frame differencing technique. Second, the object tracking method is applied and the speed is estimated based on the displacement of the object-s centroid. Several assumptions are listed to simplify the transformation of 2D images from 3D real-world images. The results obtained from the experiment have been compared to the estimated ground truth. From this experiment, it exhibits that the proposed algorithm has achieved the velocity accuracy estimation of about ± 1.7 km/h.
[1] B. Coifman, D. Beymer, P. McLauchlan and J. Malik, "A real-time
computer vision system for vehicle tracking and traffic surveillance,"
Transportation Research Part C, vol.6, no. 4, pp. 777-782,1998.
[2] D. Bauer, A. N. Belbachir and N. Donath, et al., "Embedded Vehicle
Speed Estimation System Using an Asynchronous Temporal Contrast
Vision Sensor," EURASIP J. on Embedded Systems, vol. 2007, Article
ID 82174, 12 pages, 2007.
[3] J. C. Tai, S. T. Tseng, C. P. Lin and K. T. Song, "Real-time image
tracking for automatic traffic monitoring and enforcement applications,"
Image Vis. Comput., vol. 22, pp. 485, Jun 2004.
[4] D. J. Dailey, F. W. Cathey and S. Pumrin, "An algorithm to estimate
mean traffic speed using uncalibrated cameras," IEEE Trans. on
Intelligent Transportation Systems, vol. 1, no. 2, pp. 98-107, June 2000.
[5] M. Bramberger, B. Rinner and H. Schwabach, "An embedded smart
camera on a scalable heterogeneous multi-DSP system", Proc. of the
European DSP Education and Research Symp. (EDERS2004), Nov
2004.
[6] M. Litzenberger, A. N. Belbachir, P. Schon and C. Posch, "Embedded
smart camera for high speed vision," Proc. of First ACM/IEEE
International Conference on Distributed Smart Camera, Sept 2007, pp.
81-89.
[7] T. N. Schoepflin and D. J. Dailey, "Dynamic camera calibration of
roadside traffic management cameras for vehicle speed estimation,"
IEEE Trans. on Intelligent Transportation Systems, vol. 4, no. 2,pp. 90-
98, June 2003.
[8] F. W. Cathey and D. J. Dailey, "A novel technique to dynamically
measure vehicle speed using uncalibrated roadway cameras," Proc. of
IEEE Intelligent Vehicles Symp., June 2005, pp 777-782.
[9] A. A. H. Ab-Rahman, U. U. Sheikh and M. N. Maliki, et al., "Vestro:
Velocity estimation using stereoscopic vision," Proc. of 1st Conference
on Computers, Communication and Signal Processing, Nov. 2005,
pp.120 -124.
[10] L. Grammatikopoulos, G. Karras and E. Petsa, "Automatic estimation of
vehicle speed from uncalibrated video sequences," Proc. of International
Symp. on Modern Technologies, Education and Professional Practice in
Geodesy and Related Fields, Nov. 2005, pp. 332-338.
[11] U. U. Sheikh and S. A. R. Abu-Bakar, "Three-dimensional pose
estimation from two-dimensional monocular camera images for vehicle
classification", Proc. of 6th WSEAS International Conference on Circuits,
Systems, Electronics, Control and Signal Processing, Dec 2007, pp. 356-
361.
[12] H. A. Rahim, U. U. Sheikh, R. B. Ahmad, A. S. M. Zain and W. N. S. F.
W. Ariffin, "Vehicle speed detection using frame differencing for smart
surveillance system (Accepted for publication)," to be published.
[13] H. A. Rahim, U. U. Sheikh, R. B. Ahmad and A. S. M. Zain, "An
adapted pointed based for vehicle speed estimation in linear spacing
(Accepted for publication)," to be published.
[1] B. Coifman, D. Beymer, P. McLauchlan and J. Malik, "A real-time
computer vision system for vehicle tracking and traffic surveillance,"
Transportation Research Part C, vol.6, no. 4, pp. 777-782,1998.
[2] D. Bauer, A. N. Belbachir and N. Donath, et al., "Embedded Vehicle
Speed Estimation System Using an Asynchronous Temporal Contrast
Vision Sensor," EURASIP J. on Embedded Systems, vol. 2007, Article
ID 82174, 12 pages, 2007.
[3] J. C. Tai, S. T. Tseng, C. P. Lin and K. T. Song, "Real-time image
tracking for automatic traffic monitoring and enforcement applications,"
Image Vis. Comput., vol. 22, pp. 485, Jun 2004.
[4] D. J. Dailey, F. W. Cathey and S. Pumrin, "An algorithm to estimate
mean traffic speed using uncalibrated cameras," IEEE Trans. on
Intelligent Transportation Systems, vol. 1, no. 2, pp. 98-107, June 2000.
[5] M. Bramberger, B. Rinner and H. Schwabach, "An embedded smart
camera on a scalable heterogeneous multi-DSP system", Proc. of the
European DSP Education and Research Symp. (EDERS2004), Nov
2004.
[6] M. Litzenberger, A. N. Belbachir, P. Schon and C. Posch, "Embedded
smart camera for high speed vision," Proc. of First ACM/IEEE
International Conference on Distributed Smart Camera, Sept 2007, pp.
81-89.
[7] T. N. Schoepflin and D. J. Dailey, "Dynamic camera calibration of
roadside traffic management cameras for vehicle speed estimation,"
IEEE Trans. on Intelligent Transportation Systems, vol. 4, no. 2,pp. 90-
98, June 2003.
[8] F. W. Cathey and D. J. Dailey, "A novel technique to dynamically
measure vehicle speed using uncalibrated roadway cameras," Proc. of
IEEE Intelligent Vehicles Symp., June 2005, pp 777-782.
[9] A. A. H. Ab-Rahman, U. U. Sheikh and M. N. Maliki, et al., "Vestro:
Velocity estimation using stereoscopic vision," Proc. of 1st Conference
on Computers, Communication and Signal Processing, Nov. 2005,
pp.120 -124.
[10] L. Grammatikopoulos, G. Karras and E. Petsa, "Automatic estimation of
vehicle speed from uncalibrated video sequences," Proc. of International
Symp. on Modern Technologies, Education and Professional Practice in
Geodesy and Related Fields, Nov. 2005, pp. 332-338.
[11] U. U. Sheikh and S. A. R. Abu-Bakar, "Three-dimensional pose
estimation from two-dimensional monocular camera images for vehicle
classification", Proc. of 6th WSEAS International Conference on Circuits,
Systems, Electronics, Control and Signal Processing, Dec 2007, pp. 356-
361.
[12] H. A. Rahim, U. U. Sheikh, R. B. Ahmad, A. S. M. Zain and W. N. S. F.
W. Ariffin, "Vehicle speed detection using frame differencing for smart
surveillance system (Accepted for publication)," to be published.
[13] H. A. Rahim, U. U. Sheikh, R. B. Ahmad and A. S. M. Zain, "An
adapted pointed based for vehicle speed estimation in linear spacing
(Accepted for publication)," to be published.
@article{"International Journal of Information, Control and Computer Sciences:49838", author = "H. A. Rahim and U. U. Sheikh and R. B. Ahmad and A. S. M. Zain", title = "Vehicle Velocity Estimation for Traffic Surveillance System", abstract = "This paper describes an algorithm to estimate realtime vehicle velocity using image processing technique from the known camera calibration parameters. The presented algorithm involves several main steps. First, the moving object is extracted by utilizing frame differencing technique. Second, the object tracking method is applied and the speed is estimated based on the displacement of the object-s centroid. Several assumptions are listed to simplify the transformation of 2D images from 3D real-world images. The results obtained from the experiment have been compared to the estimated ground truth. From this experiment, it exhibits that the proposed algorithm has achieved the velocity accuracy estimation of about ± 1.7 km/h.
", keywords = "camera calibration, object tracking, velocity estimation, video image processing", volume = "4", number = "9", pages = "1383-4", }
