Detail publikace

Fully Automated Real-Time Vehicles Detection and Tracking with Lanes Analysis

SOCHOR, J.

Originální název

Fully Automated Real-Time Vehicles Detection and Tracking with Lanes Analysis

Anglický název

Fully Automated Real-Time Vehicles Detection and Tracking with Lanes Analysis

Jazyk

en

Originální abstrakt

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. 

Anglický abstrakt

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. 

Dokumenty

BibTex


@inproceedings{BUT111628,
  author="Jakub {Sochor}",
  title="Fully Automated Real-Time Vehicles Detection and Tracking with Lanes Analysis",
  annote="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. ",
  address="Technical University Wien",
  booktitle="Proceedings of CESCG 2014",
  chapter="111628",
  edition="NEUVEDEN",
  howpublished="print",
  institution="Technical University Wien",
  year="2014",
  month="july",
  pages="59--66",
  publisher="Technical University Wien",
  type="conference paper"
}