International Journal of Computer Vision

, Volume 65, Issue 1–2, pp 43–72 | Cite as

A Comparison of Affine Region Detectors

  • K. Mikolajczyk
  • T. Tuytelaars
  • C. Schmid
  • A. Zisserman
  • J. Matas
  • F. Schaffalitzky
  • T. Kadir
  • L. Van Gool
Article
First Online:
Received:
Revised:
Accepted:

Abstract

The paper gives a snapshot of the state of the art in affine covariant region detectors, and compares their performance on a set of test images under varying imaging conditions. Six types of detectors are included: detectors based on affine normalization around Harris  (Mikolajczyk and  Schmid, 2002; Schaffalitzky and  Zisserman, 2002) and Hessian points  (Mikolajczyk and  Schmid, 2002), a detector of ‘maximally stable extremal regions', proposed by Matas et al. (2002); an edge-based region detector  (Tuytelaars and Van Gool, 1999) and a detector based on intensity extrema (Tuytelaars and Van Gool, 2000), and a detector of ‘salient regions', proposed by Kadir, Zisserman and Brady (2004). The performance is measured against changes in viewpoint, scale, illumination, defocus and image compression.

The objective of this paper is also to establish a reference test set of images and performance software, so that future detectors can be evaluated in the same framework.

Keywords

affine region detectors invariant image description local features performance evaluation 
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Copyright information

© Springer Science + Business Media, Inc. 2005

Authors and Affiliations

  • K. Mikolajczyk
    • 1
  • T. Tuytelaars
    • 2
  • C. Schmid
    • 4
  • A. Zisserman
    • 1
  • J. Matas
    • 3
  • F. Schaffalitzky
    • 1
  • T. Kadir
    • 1
  • L. Van Gool
    • 2
  1. 1.University of OxfordOxfordUnited Kingdom
  2. 2.University of LeuvenLeuvenBelgium
  3. 3.Czech Technical UniversityPragueCzech Republic
  4. 4.INRIA, GRAVIR-CNRSMontbonnotFrance

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