Automated Recognition of Railroad Infrastructure in Rural Areas from LIDAR Data

@article{Arastounia2015AutomatedRO,
  title={Automated Recognition of Railroad Infrastructure in Rural Areas from LIDAR Data},
  author={Mostafa Arastounia},
  journal={Remote Sensing},
  year={2015},
  volume={7},
  pages={14916-14938}
}
This study is aimed at developing automated methods to recognize railroad infrastructure from 3D LIDAR data. Railroad infrastructure includes rail tracks, contact cables, catenary cables, return current cables, masts, and cantilevers. The LIDAR dataset used in this study is acquired by placing an Optech Lynx mobile mapping system on a railcar, operating at 125 km/h. The acquired dataset covers 550 meters of Austrian rural railroad corridor comprising 31 railroad key elements and containing only… CONTINUE READING
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Key Quantitative Results

  • The results indicate that 100% accuracy and 100% precision at the object level and an average of 96.4% accuracy and an average of 97.1% precision at point cloud level are achieved.
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