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.
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© 2015 Springer International Publishing Switzerland
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Berg, A., Öfjäll, K., Ahlberg, J., Felsberg, M. (2015). Detecting Rails and Obstacles Using a Train-Mounted Thermal Camera. In: Paulsen, R., Pedersen, K. (eds) Image Analysis. SCIA 2015. Lecture Notes in Computer Science(), vol 9127. Springer, Cham. https://doi.org/10.1007/978-3-319-19665-7_42
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DOI: https://doi.org/10.1007/978-3-319-19665-7_42
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