Article

An Affine Invariant Interest Point Detector

Authors:

K. Mikolajczyk,

C. SchmidAuthors Info & Claims

ECCV '02: Proceedings of the 7th European Conference on Computer Vision-Part I

Pages 128 - 142

Published: 28 May 2002 Publication History

Abstract

This paper presents a novel approach for detecting affine invariant interest points. Our method can deal with significant affine transformations including large scale changes. Such transformations introduce significant changes in the point location as well as in the scale and the shape of the neighbourhood of an interest point. Our approach allows to solve for these problems simultaneously. It is based on three key ideas : 1) The second moment matrix computed in a point can be used to normalize a region in an affine invariant way (skew and stretch). 2) The scale of the local structure is indicated by local extrema of normalized derivatives over scale. 3) An affine-adapted Harris detector determines the location of interest points. A multi-scale version of this detector is used for initialization. An iterative algorithm then modifies location, scale and neighbourhood of each point and converges to affine invariant points. For matching and recognition, the image is characterized by a set of affine invariant points; the affine transformation associated with each point allows the computation of an affine invariant descriptor which is also invariant to affine illumination changes. A quantitative comparison of our detector with existing ones shows a significant improvement in the presence of large affine deformations. Experimental results for wide baseline matching show an excellent performance in the presence of large perspective transformations including significant scale changes. Results for recognition are very good for a database with more than 5000 images.

References

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K. Mikolajczyk and C. Schmid. Indexing based on scale invariant interest points. In Proceedings of the 8th International Conference on Computer Vision, Vancouver, Canada , pages 525-531, 2001.

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Test sequences. http://www.inrialpes.fr/movi/people/Mikolajczyk/Database/

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Index Terms

An Affine Invariant Interest Point Detector
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
  2. Computer graphics
    1. Image manipulation

Index terms have been assigned to the content through auto-classification.

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cover image Guide Proceedings

ECCV '02: Proceedings of the 7th European Conference on Computer Vision-Part I

May 2002

810 pages

ISBN:3540437452

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 28 May 2002

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https://dl.acm.org/doi/10.1007/s11263-018-1125-z
Álvarez-Bermejo JMorales-Santos DCastillo-Morales EParrilla LLópez-Ramos J(2019)Efficient image-based analysis of fruit surfaces using CCD cameras and smartphonesThe Journal of Supercomputing10.1007/s11227-018-2284-y75:3(1026-1037)Online publication date: 1-Mar-2019
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