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Mathematical Morphology on Irregularly Sampled Data Applied to Segmentation of 3D Point Clouds of Urban Scenes

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Mathematical Morphology and Its Applications to Signal and Image Processing (ISMM 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11564))

Abstract

This paper proposes an extension of mathematical morphology on irregularly sampled signals to 3D point clouds. The proposed method is applied to the segmentation of urban scenes to show its applicability to the analysis of point cloud data. Applying the proposed operators has the desirable side-effect of homogenizing signals that are sampled heterogeneously. In experiments we show that the proposed segmentation algorithm yields good results on the Paris-rue-Madame database and is robust in terms of sampling density, i.e. yielding similar labelings for more sparse samplings of the same scene.

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Notes

  1. 1.

    ©2014 MINES ParisTech. MINES ParisTech created this special set of 3D MLS data for the purpose of detection-segmentation-classification research activities.

References

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Acknowledgement

Teo Asplund was funded through grant 2014-5983 from the Swedish Research Council.

Author information

Authors and Affiliations

  1. Centre for Image Analysis, Division of Visual Information and Interaction, Uppsala University, Uppsala, Sweden

    Teo Asplund & Robin Strand

  2. Terra3D, 36 Boulevard de la Bastille, 75012, Paris, France

    Andrés Serna

  3. MINES ParisTech, PSL Research University, CMM - Centre for Mathematical Morphology, 35 rue Saint Honoré, Fontainebleau, France

    Beatriz Marcotegui

  4. Flagship Biosciences Inc., Westminster, Colorado, USA

    Cris L. Luengo Hendriks

Authors
  1. Teo Asplund
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  2. Andrés Serna
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  3. Beatriz Marcotegui
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  4. Robin Strand
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  5. Cris L. Luengo Hendriks
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Corresponding author

Correspondence to Teo Asplund .

Editor information

Editors and Affiliations

  1. Universität des Saarlandes, Saarbrücken, Germany

    Bernhard Burgeth

  2. Forschungszentrum Jülich GmbH, Jülich, Germany

    Andreas Kleefeld

  3. Université de Strasbourg, Illkirch Cedex, France

    Benoît Naegel

  4. Université de Reims Champagne-Ardenne, Reims Cedex 2, France

    Nicolas Passat

  5. Université Paris-Est, Noisy le Grand Cedex, France

    Benjamin Perret

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Asplund, T., Serna, A., Marcotegui, B., Strand, R., Luengo Hendriks, C.L. (2019). Mathematical Morphology on Irregularly Sampled Data Applied to Segmentation of 3D Point Clouds of Urban Scenes. In: Burgeth, B., Kleefeld, A., Naegel, B., Passat, N., Perret, B. (eds) Mathematical Morphology and Its Applications to Signal and Image Processing. ISMM 2019. Lecture Notes in Computer Science(), vol 11564. Springer, Cham. https://doi.org/10.1007/978-3-030-20867-7_29

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  • DOI: https://doi.org/10.1007/978-3-030-20867-7_29

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-20866-0

  • Online ISBN: 978-3-030-20867-7

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