A Robust Interest Points Matching Algorithm

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A Robust Interest Points Matching Algorithm
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 points: 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.
Il-Kyun Jung, Simon Lacroix
Added 15 Oct 2009
Updated 31 Oct 2009
Type Conference
Year 2001
Where ICCV
Authors Il-Kyun Jung, Simon Lacroix
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