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European Conference on Computer Vision

ECCV 2010: Trends and Topics in Computer Vision pp 463–476Cite as

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Fast Organization of Large Photo Collections Using CUDA

Fast Organization of Large Photo Collections Using CUDA

  • Tim Johnson17,
  • Pierre Fite-Georgel17,
  • Rahul Raguram17 &
  • …
  • Jan-Michael Frahm17 
  • Conference paper
  • 1992 Accesses

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

Abstract

In this paper, we introduce a system for the automatic organization of photo collections consisting of millions of images downloaded from the Internet. To our knowledge, this is the first approach that tackles this problem exclusively through the use of general-purpose GPU computing techniques. By leveraging the inherent parallelism of the problem and through the use of efficient GPU-based algorithms, our system is able to effectively summarize datasets containing up to three million images in approximately 16 hours on a single PC, which is orders of magnitude faster compared to current state of the art techniques. In this paper, we present the various algorithmic considerations and design aspects of our system, and describe in detail the various steps of the processing pipeline. Additionally, we demonstrate the effectiveness of the system by showing results for a variety of real-world datasets, ranging from the scale of a single landmark, to that of an entire city.

Keywords

  • Binary Code
  • Fundamental Matrix
  • Query Expansion
  • Thread Block
  • Virtual Image

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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Author information

Authors and Affiliations

  1. Department of Computer Science, University of North Carolina at Chapel Hill, USA

    Tim Johnson, Pierre Fite-Georgel, Rahul Raguram & Jan-Michael Frahm

Authors
  1. Tim Johnson
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  2. Pierre Fite-Georgel
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  3. Rahul Raguram
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  4. Jan-Michael Frahm
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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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Johnson, T., Fite-Georgel, P., Raguram, R., Frahm, JM. (2012). Fast Organization of Large Photo Collections 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_36

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  • DOI: https://doi.org/10.1007/978-3-642-35740-4_36

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  • Print ISBN: 978-3-642-35739-8

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