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Speeding Up SURF

  • Peter Abeles
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8034)

Abstract

SURF has emerged as one of the more popular feature descriptors and detectors in recent years. While considerably faster than SIFT, it is still considered too computationally expensive for many applications. In this paper, several algorithmic changes are proposed to create two new SURF like descriptors and a SURF like feature detector. The proposed changes have comparable stability to the reference implementation, yet a byte code implementation is able run several times faster than the native reference implementation and faster than all other open source implementations tested.

Keywords

Interest Point Reference Library Runtime Performance Interest Point Detection Algorithmic Change 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Peter Abeles
    • 1
  1. 1.Robotic InceptionAustralia

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