Clustering and visualization of non-classified points from LiDAR data for helicopter navigation

Eisenkeil, Ferdinand; Schafhitzel, Tobias; Kühne, Uwe; Deussen, Oliver

Clustering and visualization of non-classified points from LiDAR data for helicopter navigation

Dateien

Eisenkeil_0-263482.pdfGröße: 908.6 KBDownloads: 355

Datum

2014

Autor:innen

Eisenkeil, Ferdinand

Schafhitzel, Tobias

Kühne, Uwe

Deussen, Oliver

Open Access-Veröffentlichung

Open Access Green

Sammlungen

Informatik und Informationswissenschaft

Publikationstyp

Beitrag zu einem Konferenzband

Publikationsstatus

Published

Erschienen in

KADAR, Ivan, ed.. Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII ; 5–8 May 2014 Baltimore, Maryland, United States. Bellingham: SPIE, 2014, 90910V. Proceedings of SPIE. 9091. ISBN 978-1-62841-028-0. Available under: doi: 10.1117/12.2050497

Zusammenfassung

In this paper we propose a dynamic DBSCAN-based method to cluster and visualize unclassified and potential dangerous obstacles in data sets recorded by a LiDAR sensor. The sensor delivers data sets in a short time interval, so a spatial superposition of multiple data sets is created. We use this superposition to create clusters incrementally. Knowledge about the position and size of each cluster is used to fuse clusters and the stabilization of clusters within multiple time frames. Cluster stability is a key feature to provide a smooth and un-distracting visualization for the pilot. Only a few lines are indicating the position of threatening unclassified points, where a hazardous situation for the helicopter could happen, if it comes too close. Clustering and visualization form a part of an entire synthetic vision processing chain, in which the LiDAR points support the generation of a real-time synthetic view of the environment

Fachgebiet (DDC)

004 Informatik

Schlagwörter

LiDAR, Density-based Clustering, Head-mounted Displays, Visualization, R-Functions, Synthetic Vision

Konferenz

Sensor/Information Fusion, and Target Recognition XXIII, 5. Mai 2014 - 8. Mai 2014, Baltimore

Zitieren

ISO 690

EISENKEIL, Ferdinand, Tobias SCHAFHITZEL, Uwe KÜHNE, Oliver DEUSSEN, 2014. Clustering and visualization of non-classified points from LiDAR data for helicopter navigation. Sensor/Information Fusion, and Target Recognition XXIII. Baltimore, 5. Mai 2014 - 8. Mai 2014. In: KADAR, Ivan, ed.. Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII ; 5–8 May 2014 Baltimore, Maryland, United States. Bellingham: SPIE, 2014, 90910V. Proceedings of SPIE. 9091. ISBN 978-1-62841-028-0. Available under: doi: 10.1117/12.2050497

BibTex

@inproceedings{Eisenkeil2014Clust-30014,
  year={2014},
  doi={10.1117/12.2050497},
  title={Clustering and visualization of non-classified points from LiDAR data for helicopter navigation},
  number={9091},
  isbn={978-1-62841-028-0},
  publisher={SPIE},
  address={Bellingham},
  series={Proceedings of SPIE},
  booktitle={Signal Processing, Sensor/Information Fusion, and Target Recognition XXIII ; 5–8 May 2014 Baltimore, Maryland, United States},
  editor={Kadar, Ivan},
  author={Eisenkeil, Ferdinand and Schafhitzel, Tobias and Kühne, Uwe and Deussen, Oliver},
  note={Article Number: 90910V}
}

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Universitätsbibliographie

Ja