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Asian Conference on Computer Vision

ACCV 2010: Computer Vision – ACCV 2010 pp 474–485Cite as

Fast Recovery of Weakly Textured Surfaces from Monocular Image Sequences

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6495))

Abstract

We present a method for vision-based recovery of three-dimensional structures through simultaneous model reconstruction and camera position tracking from monocular images. Our approach does not rely on robust feature detecting schemes (such as SIFT, KLT etc.), but works directly on intensity values in the captured images. Thus, it is well-suited for reconstruction of surfaces that exhibit only minimal texture due to partial homogeneity of the surfaces. Our method is based on a well-known optimization technique, which has been implemented in an efficient yet flexible way, in order to achieve high performance while ensuring extensibility.

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Author information

Authors and Affiliations

  1. Institut für Informatik, Technische Universität München, Boltzmannstraße 3, D-85748, Garching bei München, Germany

    Oliver Ruepp & Darius Burschka

Authors
  1. Oliver Ruepp
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  2. Darius Burschka
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Technion – Israel Institute of Technology, 32000, Haifa, Israel

    Ron Kimmel

  2. The University of Auckland, 37 Kohimarama Road, 1071, Mission Bay, Auckland, New Zealand

    Reinhard Klette

  3. National Institute of Informatics, 1018430, Chiyoda, Tokyo, Japan

    Akihiro Sugimoto

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Ruepp, O., Burschka, D. (2011). Fast Recovery of Weakly Textured Surfaces from Monocular Image Sequences. In: Kimmel, R., Klette, R., Sugimoto, A. (eds) Computer Vision – ACCV 2010. ACCV 2010. Lecture Notes in Computer Science, vol 6495. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19282-1_38

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  • DOI: https://doi.org/10.1007/978-3-642-19282-1_38

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19281-4

  • Online ISBN: 978-3-642-19282-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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