NDLI: A robust interest points matching algorithm

Content Provider	IEEE Xplore Digital Library
Author	Il-Kyun Jung Lacroix, S.
Copyright Year	2001
Description	Author affiliation: Lab. d'Autom. et d'Anal. des Syst., CNRS, Toulouse, France (Il-Kyun Jung)
Abstract	This paper presents an algorithm that matches interest points detected on a pair of grey level images taken from arbitrary points of view. First matching hypotheses are generated using a similarity measure of the interest points. Hypotheses are confirmed using local groups of interest paints: group matches are based on a measure defined on an affine transformation estimate and on a correlation coefficient computed on the intensity of the interest points. Once a reliable match has been determined for a given interest point and the corresponding local group, new group matches are found by propagating the estimated affine transformation. The algorithm has been widely tested under various image transformations: it provides dense matches and is very robust to outliers, i.e. interest points generated by noise or present in only one image because of occlusions or non overlap.
Sponsorship	IEEE Comput. Soc. Tech. Committee on Pattern Anal. & Machine Intelligence
Starting Page	538
Ending Page	543
File Size	880412
Page Count	6
File Format	PDF
ISBN	0769511430
DOI	10.1109/ICCV.2001.937672
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-07-07
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Noise robustness Information retrieval Image retrieval Image databases Detectors Autocorrelation Testing Noise generators Computer vision Feature extraction
Content Type	Text
Resource Type	Article

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