Paper Info
Title
Quantitative Comparison Of Affine Invariant Feature Matching
Abstract
It is a key problem in computer vision to apply accurate feature matchers between images. Thus the comparison of such matchers is essential. There are several survey papers in the field, this study extends one of those: the aim of this paper is to compare competitive techniques on the ground truth (GT) data generated by our structured-light 3D scanner with a rotating table. The discussed quantitative comparison is based on real images of six rotating 3D objects. The rival detectors in the comparison are as follows: Harris-Laplace, Hessian-Laplace, Harris-Affine, Hessian-Affine, IBR, EBR, SURF, and MSER.
Year
DOI
Venue
2017
10.5220/0006263005150522
PROCEEDINGS OF THE 12TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISIGRAPP 2017), VOL 6
Keywords
Field
DocType
Quantitative Comparison, Feature Points, Matching
Affine transformation,Affine shape adaptation,Harris affine region detector,Affine combination,Pattern recognition,Affine coordinate system,Computer science,Artificial intelligence,Hessian affine region detector,Affine hull,Affine geometry of curves
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Zoltán Pusztai182.58
Levente Hajder24312.55