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Detecting Rails and Obstacles Using a Train-Mounted Thermal Camera

  • Amanda Berg
  • Kristoffer Öfjäll
  • Jörgen Ahlberg
  • Michael Felsberg
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9127)

Abstract

We propose a method for detecting obstacles on the railway in front of a moving train using a monocular thermal camera. The problem is motivated by the large number of collisions between trains and various obstacles, resulting in reduced safety and high costs. The proposed method includes a novel way of detecting the rails in the imagery, as well as a way to detect anomalies on the railway. While the problem at a first glance looks similar to road and lane detection, which in the past has been a popular research topic, a closer look reveals that the problem at hand is previously unaddressed. As a consequence, relevant datasets are missing as well, and thus our contribution is two-fold: We propose an approach to the novel problem of obstacle detection on railways and we describe the acquisition of a novel data set.

Keywords

Thermal imaging Computer vision Train safety Railway detection Anomaly detection Obstacle detection 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Amanda Berg
    • 1
    • 2
  • Kristoffer Öfjäll
    • 1
  • Jörgen Ahlberg
    • 1
    • 2
  • Michael Felsberg
    • 1
  1. 1.Computer Vision Laboratory, Department of Electrical EngineeringLinköping UniversityLinköpingSweden
  2. 2.Termisk Systemteknik ABLinköpingSweden

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