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European Conference on Computer Vision

ECCV 2010: Trends and Topics in Computer Vision pp 398–410Cite as

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Comparison of Dense Stereo Using CUDA

Comparison of Dense Stereo Using CUDA

  • Ke Zhu17,
  • Matthias Butenuth18 &
  • Pablo d’Angelo19 
  • Conference paper
  • 2243 Accesses

  • 2 Citations

Part of the Lecture Notes in Computer Science book series (LNIP,volume 6554)

Abstract

In this paper, a local and a global dense stereo matching method, implemented using Compute Unified Device Architecture (CUDA), are presented, analyzed and compared. The purposed work shows the general strategy of the parallelization of matching methods on GPUs and the tradeoff between accuracy and run-time on current GPU hardware. Two representative and widely-used methods, the Sum of Absolute Differences (SAD) method and the Semi-Global Matching (SGM) method, are used and their results are compared using the Middlebury test sets.

Keywords

  • Shared Memory
  • Global Memory
  • Thread Block
  • Epipolar Line
  • Cost Aggregation

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Author information

Authors and Affiliations

  1. Remote Sensing Technology, Technische Universit”at M”unchen, Germany

    Ke Zhu

  2. Active Safety and Driver Assistance, IAV GmbH, Germany

    Matthias Butenuth

  3. Remote Sensing Technology Institute, German Aerospace Center (DLR), Germany

    Pablo d’Angelo

Authors
  1. Ke Zhu
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  2. Matthias Butenuth
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  3. Pablo d’Angelo
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Toronto, 10 King’s College Road, M5S 3G4, Toronto, ON, Canada

    Kiriakos N. Kutulakos

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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

Zhu, K., Butenuth, M., d’Angelo, P. (2012). Comparison of Dense Stereo Using CUDA. In: Kutulakos, K.N. (eds) Trends and Topics in Computer Vision. ECCV 2010. Lecture Notes in Computer Science, vol 6554. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35740-4_31

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  • DOI: https://doi.org/10.1007/978-3-642-35740-4_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35739-8

  • Online ISBN: 978-3-642-35740-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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