Conditional random fields for urban scene classification with full waveform LiDAR data

Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

Authors

  • Joachim Niemeyer
  • Jan Dirk Wegner
  • Clément Mallet
  • Franz Rottensteiner
  • Uwe Soergel

Research Organisations

External Research Organisations

  • Université Paris-Est Créteil Val-de-Marne (UPEC)
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Details

Original languageEnglish
Title of host publicationPhotogrammetric Image Analysis, ISPRS Conference, PIA 2011, Proceedings
Pages233-244
Number of pages12
Publication statusPublished - 2011
EventISPRS Conference on Photogrammetric Image Analysis, PIA 2011 - Munich, Germany
Duration: 5 Oct 2011 → 7 Oct 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6952 LNCS
ISSN (Print)0302-9743
ISSN (electronic)1611-3349

Abstract

We propose a context-based classification method for point clouds acquired by full waveform airborne laser scanners. As these devices provide a higher point density and additional information like echo width or type of return, an accurate distinction of several object classes is possible. However, especially in dense urban areas correct labelling is a challenging task. Therefore, we incorporate context knowledge by using Conditional Random Fields. Typical object structures are learned in a training step and improve the results of the point-based classification process. We validate our approach with two real-world datasets and by a comparison to Support Vector Machines and Markov Random Fields.

Keywords

    3D Point Cloud, Classification, Conditional Random Fields, Full Waveform LiDAR, Urban

ASJC Scopus subject areas

Cite this

Conditional random fields for urban scene classification with full waveform LiDAR data. / Niemeyer, Joachim; Wegner, Jan Dirk; Mallet, Clément et al.
Photogrammetric Image Analysis, ISPRS Conference, PIA 2011, Proceedings. 2011. p. 233-244 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6952 LNCS).

Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review

Niemeyer, J, Wegner, JD, Mallet, C, Rottensteiner, F & Soergel, U 2011, Conditional random fields for urban scene classification with full waveform LiDAR data. in Photogrammetric Image Analysis, ISPRS Conference, PIA 2011, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6952 LNCS, pp. 233-244, ISPRS Conference on Photogrammetric Image Analysis, PIA 2011, Munich, Germany, 5 Oct 2011. https://doi.org/10.1007/978-3-642-24393-6_20
Niemeyer, J., Wegner, J. D., Mallet, C., Rottensteiner, F., & Soergel, U. (2011). Conditional random fields for urban scene classification with full waveform LiDAR data. In Photogrammetric Image Analysis, ISPRS Conference, PIA 2011, Proceedings (pp. 233-244). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6952 LNCS). https://doi.org/10.1007/978-3-642-24393-6_20
Niemeyer J, Wegner JD, Mallet C, Rottensteiner F, Soergel U. Conditional random fields for urban scene classification with full waveform LiDAR data. In Photogrammetric Image Analysis, ISPRS Conference, PIA 2011, Proceedings. 2011. p. 233-244. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-24393-6_20
Niemeyer, Joachim ; Wegner, Jan Dirk ; Mallet, Clément et al. / Conditional random fields for urban scene classification with full waveform LiDAR data. Photogrammetric Image Analysis, ISPRS Conference, PIA 2011, Proceedings. 2011. pp. 233-244 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Download
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