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3D Planar RGB-D SLAM System

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Advanced Concepts for Intelligent Vision Systems (ACIVS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10016))

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Abstract

Applications such as Simultaneous Localization and Mapping (SLAM) can greatly benefit from RGB-D sensor data to produce 3D maps of the environment as well as sensor’s trajectory estimation. However, the resulting 3D points map can be cumbersome, and since indoor environments are mainly composed of planar surfaces, the idea is to use planes as building blocks for a SLAM process. This paper describes an RGB-D SLAM system benefiting from planes segmentation to generate lightweight 3D plane-based maps. Our goal is to produce reduced 3D maps composed solely of planes sections that can be used on platforms with limited memory and computation resources. We present the introduction of planar regions in a regular RGB-D SLAM system and evaluate the benefits regarding both resulting map and estimated camera trajectory.

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Author information

Authors and Affiliations

  1. IBISC Lab, Evry Val d’Essonne University, Évry, France

    Hakim ElChaoui ElGhor, David Roussel & Fakhreddine Ababsa

  2. LIMIARF Lab, Mohammed V University, Rabat, Morocco

    Hakim ElChaoui ElGhor & El-Houssine Bouyakhf

Authors
  1. Hakim ElChaoui ElGhor
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  2. David Roussel
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  3. Fakhreddine Ababsa
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  4. El-Houssine Bouyakhf
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Corresponding author

Correspondence to Hakim ElChaoui ElGhor .

Editor information

Editors and Affiliations

  1. Université Paris-Sud 11 , Orsay, France

    Jacques Blanc-Talon

  2. University of Salento , Lecce, Lecce, Italy

    Cosimo Distante

  3. Ghent University , Gent, Belgium

    Wilfried Philips

  4. CSIRO ICT Centre , Sydney, New South Wales, Australia

    Dan Popescu

  5. University of Antwerp , Wilrijk, Belgium

    Paul Scheunders

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© 2016 Springer International Publishing AG

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ElChaoui ElGhor, H., Roussel, D., Ababsa, F., Bouyakhf, EH. (2016). 3D Planar RGB-D SLAM System. In: Blanc-Talon, J., Distante, C., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2016. Lecture Notes in Computer Science(), vol 10016. Springer, Cham. https://doi.org/10.1007/978-3-319-48680-2_43

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  • DOI: https://doi.org/10.1007/978-3-319-48680-2_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48679-6

  • Online ISBN: 978-3-319-48680-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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