Track detection in 3D laser scanning data of railway infrastructure

Novel safety systems are needed to meet the growing demand of railway operation. In this paper we introduce general techniques for the detection of tracks and their components in 3D laser scanning data. These techniques make use of feature based methods, such as support vector machines, as well as model based methods, such as template matching. The focus of this work are robust and precise detectors for infrastructure elements, such as rails, tracks, closure rails, and frogs. These parts can be used for both, track maintenance and train-borne localization. The approach is evaluated experimentally on 3D laser scanning data and compared with a reference system. Furthermore, the approach is generic such that it can be used for data of any suitable laser scanning system.