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GPU-ASIFT: A fast fully affine-invariant feature extraction algorithm

  • Valeriu Codreanu
    ,
  • Feng Dong
    ,
  • Baoquan Liu
    ,
  • Jos B.T.M. Roerdink
    ,
  • David Williams
    ,
  • Po Yang
  • University of Groningen
    ,
  • University of Bedfordshire
    ,
  • Rotasoft Inc
Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Abstract

This paper presents a method that takes advantage of powerful graphics hardware to obtain fully affine-invariant image feature detection and matching. The chosen approach is the accurate, but also very computationally expensive, ASIFT algorithm. We have created a CUDA version of this algorithm that is up to 70 times faster than the original implementation, while keeping the algorithm's accuracy close to that of ASIFT. It's matching performance is therefore much better than that of other non-fully affine-invariant algorithms. Also, this approach was adapted to fit the multi-GPU paradigm in order to assess the acceleration potential from modern GPU clusters.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Original language

English

Article number

6641456

Pages from-to (Number of pages)

Pages 474-481 (8 pages)

Publication milestones

  • Published - 21/10/2013

Publication status

Published - 21/10/2013

Publication series

  • Publication series name: Proceedings of the 2013 International Conference on High Performance Computing and Simulation, HPCS 2013
9781479908363

External Publication IDs

  • Scopus: 84888022070

Host publication title

Proceedings of the 2013 International Conference on High Performance Computing and Simulation, HPCS 2013