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http://dx.doi.org/10.7848/ksgpc.2015.33.2.111

Railway Track Extraction from Mobile Laser Scanning Data  

Yoonseok, Jwa (Dept. of Geomatics Engineering, York University)
Gunho, Sohn (Dept. of Geomatics Engineering, York University)
Jong Un, Won (Green Transport & Logistics Institute, Korea Railroad Research Institute)
Wonchoon, Lee (Detail Map Development Team, HyundaiMNSoft)
Nakhyeon, Song (Softgraphy)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.33, no.2, 2015 , pp. 111-122 More about this Journal
Abstract
This study purposed on introducing a new automated solution for detecting railway tracks and reconstructing track models from the mobile laser scanning data. The proposed solution completes following procedures; the study initiated with detecting a potential railway region, called Region Of Interest (ROI), and approximating the orientation of railway track trajectory with the raw data. At next, the knowledge-based detection of railway tracks was performed for localizing track candidates in the first strip. In here, a strip -referring the local track search region- is generated in the orthogonal direction to the orientation of track trajectory. Lastly, an initial track model generated over the candidate points, which were detected by GMM-EM (Gaussian Mixture Model-Expectation & Maximization) -based clustering strip- wisely grows to capture all track points of interest and thus converted into geometric track model in the tracking by detection framework. Therefore, the proposed railway track tracking process includes following key features; it is able to reduce the complexity in detecting track points by using a hypothetical track model. Also, it enhances the efficiency of track modeling process by simultaneously capturing track points and modeling tracks that resulted in the minimization of data processing time and cost. The proposed method was developed using the C++ program language and was evaluated by the LiDAR data, which was acquired from MMS over an urban railway track area with a complex railway scene as well.
Keywords
Railway Track Modeling; GMM-EM based Clustering; Mobile Laser Scanning Data;
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