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Fast Range Image Segmentation and Smoothing Using Approximate Surface Reconstruction and Region Growing

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Intelligent Autonomous Systems 12

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 194))

Abstract

Decomposing sensory measurements into relevant parts is a fundamental prerequisite for solving complex tasks, e.g., in the field of mobile manipulation in domestic environments. In this paper, we present a fast approach to surface reconstruction in range images by means of approximate polygonal meshing. The obtained local surface information and neighborhoods are then used to 1) smooth the underlying measurements, and 2) segment the image into planar regions and other geometric primitives. An evaluation using publicly available data sets shows that our approach does not rank behind state-of-the-art algorithms while allowing to process range images at high frame rates.

This research has been partially funded by the FP7 ICT-2007.2.2 project ECHORD (grant agreement 231143) experiment ActReMa.

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Authors and Affiliations

  1. Autonomous Intelligent Systems Group, University of Bonn, Bonn, Germany

    Dirk Holz & Sven Behnke

Authors
  1. Dirk Holz
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  2. Sven Behnke
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Corresponding author

Correspondence to Dirk Holz .

Editor information

Editors and Affiliations

  1. , School of Information and Communication, Sungkyunkwan University, 300 Chunchun-Dong Jangan-Ku, Kyunggi-Do, 440-746, Korea, Republic of (South Korea)

    Sukhan Lee

  2. Science and Technology, Daegu Gyeongbuk Institute of, 50-1, Sang-Ri, Hyeonpung-Myeon, Dalseong-Gun, Daegu, 711-873, Korea, Republic of (South Korea)

    Hyungsuck Cho

  3. Konkuk University, Neungdong-ro, Gwangjin-gu 120, Seoul, 143-701, Korea, Republic of (South Korea)

    Kwang-Joon Yoon

  4. , Department of Electronics Engineering, Pusan National University, Geum Jeong-ku, Pusan, 609-735, Korea, Republic of (South Korea)

    Jangmyung Lee

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Holz, D., Behnke, S. (2013). Fast Range Image Segmentation and Smoothing Using Approximate Surface Reconstruction and Region Growing. In: Lee, S., Cho, H., Yoon, KJ., Lee, J. (eds) Intelligent Autonomous Systems 12. Advances in Intelligent Systems and Computing, vol 194. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33932-5_7

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  • DOI: https://doi.org/10.1007/978-3-642-33932-5_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33931-8

  • Online ISBN: 978-3-642-33932-5

  • eBook Packages: EngineeringEngineering (R0)

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