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Proceedings Paper

A vision-based approach for tramway rail extraction
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Paper Abstract

The growing traffic density in cities fuels the desire for collision assessment systems on public transportation. For this application, video analysis is broadly accepted as a cornerstone. For trams, the localization of tramway tracks is an essential ingredient of such a system, in order to estimate a safety margin for crossing traffic participants. Tramway-track detection is a challenging task due to the urban environment with clutter, sharp curves and occlusions of the track. In this paper, we present a novel and generic system to detect the tramway track in advance of the tram position. The system incorporates an inverse perspective mapping and a-priori geometry knowledge of the rails to find possible track segments. The contribution of this paper involves the creation of a new track reconstruction algorithm which is based on graph theory. To this end, we define track segments as vertices in a graph, in which edges represent feasible connections. This graph is then converted to a max-cost arborescence graph, and the best path is selected according to its location and additional temporal information based on a maximum a-posteriori estimate. The proposed system clearly outperforms a railway-track detector. Furthermore, the system performance is validated on 3,600 manually annotated frames. The obtained results are promising, where straight tracks are found in more than 90% of the images and complete curves are still detected in 35% of the cases.

Paper Details

Date Published: 4 March 2015
PDF: 13 pages
Proc. SPIE 9407, Video Surveillance and Transportation Imaging Applications 2015, 94070R (4 March 2015); doi: 10.1117/12.2075641
Show Author Affiliations
Matthijs H. Zwemer, ViNotion B.V. (Netherlands)
Technische Univ. Eindhoven (Netherlands)
Dennis W. J. M. van de Wouw, ViNotion B.V. (Netherlands)
Technische Univ. Eindhoven (Netherlands)
Egbert G. T. Jaspers, ViNotion B.V. (Netherlands)
Sveta Zinger, Technische Univ. Eindhoven (Netherlands)
Peter H. N. de With, Technische Univ. Eindhoven (Netherlands)


Published in SPIE Proceedings Vol. 9407:
Video Surveillance and Transportation Imaging Applications 2015
Robert P. Loce; Eli Saber, Editor(s)

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