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A comparison of affine region detectors (2005)

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by K. Mikolajczyk , T. Tuytelaars , C. Schmid , A. Zisserman , J. Matas , F. Schaffalitzky , T. Kadir , L. Van Gool
Venue:International Journal of Computer Vision
Citations:364 - 19 self
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BibTeX

@ARTICLE{Mikolajczyk05acomparison,
    author = {K. Mikolajczyk and T. Tuytelaars and C. Schmid and A. Zisserman and J. Matas and F. Schaffalitzky and T. Kadir and L. Van Gool},
    title = {A comparison of affine region detectors},
    journal = {International Journal of Computer Vision},
    year = {2005},
    volume = {65},
    pages = {2005}
}

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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 [24, 34] and Hessian points [24], as proposed by Mikolajczyk and Schmid and by Schaffalitzky and Zisserman; a detector of ‘maximally stable extremal regions’, proposed by Matas et al. [21]; an edge-based region detector [45] and a detector based on intensity extrema [47], proposed by Tuytelaars and Van Gool; and a detector of ‘salient regions’, proposed by Kadir, Zisserman and Brady [12]. 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. 1

Keyphrases

affine region detector    future detector    reference test set    six type    test image    van gool    imaging condition    hessian point    affine covariant region detector    stable extremal region    edge-based region detector    intensity extremum    salient region    affine normalization    image compression    performance software   

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