Vision Based Anti-collision System for Rail Track Maintenance Vehicles
Maire, Frederic D. (2007) Vision Based Anti-collision System for Rail Track Maintenance Vehicles. In Cavallaro, Andrea (Ed.) IEEE Conference on Advanced Video and Signal Based Surveillance, 2007. (AVSS 2007), 5-7 September 2007, London (United Kingdom).
Maintenance trains travel in convoy. In Australia, only the first train of the convoy pays attention to the track signalization (the other convoy vehicles simply follow the preceding vehicle). Because of human errors, collisions can happen between the maintenance vehicles. Although an anticollision system based on a laser distance meter is already in operation, the existing system has a limited range due to the curvature of the tracks. In this paper, we introduce an anti-collision system based on vision. The proposed system induces a 3D model of the track as a piecewise quadratic function (with continuity constraints on the function and its derivative). The geometric constraints of the rail tracks allow the creation of a completely self-calibrating system. Although road lane marking detection algorithms perform well most of the time for rail detection, the metallic surface of a rail does not always behave like a road lane marking. Therefore we had to develop new techniques to address the specific problems of the reflectance of rails.
Impact and interest:
Citation counts are sourced monthly from and citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloads displays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Conference Paper|
|Keywords:||computer vision, railways, road vehicles, solid modelling|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology|
|Copyright Owner:||Copyright 2007 IEEE|
|Copyright Statement:||Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.|
|Deposited On:||19 Feb 2008|
|Last Modified:||29 Feb 2012 13:34|
Repository Staff Only: item control page