RESEARCH ARTICLE
A Video-Based Object Detection System for Improving Safety at Level Crossings
N. Fakhfakh*, 1, 2, L. Khoudour1, E. M. El-Koursi1, J. Jacot2, A. Dufaux2
Article Information
Identifiers and Pagination:
Year: 2011Volume: 5
First Page: 45
Last Page: 59
Publisher ID: TOTJ-5-45
DOI: 10.2174/1874447801105010045
Article History:
Received Date: 25/5/2010Revision Received Date: 23/8/2010
Acceptance Date: 29/9/2010
Electronic publication date: 6/10/2011
Collection year: 2011
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Improving transport users' safety is one of the main priorities of research into transport system attractiveness. Level crossings are one of the most critical weak point involving road and rail users' infrastructure. They have become increasingly dangerous and unsafe due to road and railway users' behavior. Furthermore, rail and highway safety professionals from several countries must deal with the same subject: providing safer level crossing. Actions are planned in order to exchange and share knowledge on existing level crossings technologies between academic organizations and industrial operators, and provide experiments for improving the management of level crossing safety and performance. This has enabled us to discuss sharing knowledge gained from research in order to improve safety at level crossings. This article provides research results about possible technological solutions to reduce the number of accidents at level crossings. As a main contribution is that we discuss and prove the effectiveness of the use of video sensing for object detection. Furthermore, we have tested and adapted a robust technique for moving object detection, which is followed by a new approach for 3D object localization.