Article citationsMore>>
Collins, R.T., Lipton, A.J., Kanade, T., Fujiyoshi, H., Duggins, D., Tsin, Y., Tolliver, D., Enomoto, N., Hasegawa, O., Burt, P. and Wixson, L. (2000) A System for Video Surveillance and Monitoring. The RoboticsInstitute, Carnegie Mellon University, Princeton, NJ.
has been cited by the following article:
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TITLE:
Image-Based Vehicle Speed Estimation
AUTHORS:
Md. Golam Moazzam, Mohammad Reduanul Haque, Mohammad Shorif Uddin
KEYWORDS:
Vehicle Detection, Speed Calculation, Background Subtraction, Vehicle Tracking
JOURNAL NAME:
Journal of Computer and Communications,
Vol.7 No.6,
May
27,
2019
ABSTRACT: Vehicle speed is an important parameter that finds tremendous application in traffic control identifying over speed vehicles with a view to reducing accidents. Many methods, such as using RADAR and LIDAR sensors have been proposed. However, these are expensive, and their accuracy is not quite satisfactory. In this paper, a video-based vehicle speed determination method is presented. The method shows satisfactory performance on standard data sets and gives that error rate of velocity estimation is within 10%.
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