Fully Automated Real-Time Vehicles Detection and Tracking with Lanes Analysis [CESCG 2014]

Jakub Sochor, supervisor: Adam Herout
GRAPH@FIT, Brno University of Technology
Corresponding authors: isochor [at] fit.vutbr.cz


This paper presents a fully automated system for traffic surveillance which is able to count passing cars, determine their direction, and the lane which they are taking. The system works without any manual input whatsoever and it is able to automatically calibrate the camera by detecting vanishing points in the video sequence. The proposed system is able to work in real time and therefore it is ready for deployment in real traffic surveillance applications. The system uses motion detection and tracking with the Kalman filter. The lane detection is based on clustering of trajectories of vehicles. The main contribution is a set of filters which a track has to pass in order to be treated as a vehicle and the full automation of the system.


  • 3rd Best Paper Award



 author = {Sochor, Jakub},
 title = {Fully Automated Real-Time Vehicles Detection and Tracking with Lanes Analysis},
 booktitle = {Proceedings of The 18th Central European Seminar on Computer
 year = {2014},
 publisher = {Technical University Wien},
 ISBN = {978-3-9502533-3-7}