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CVPR
2009
IEEE

SIFT-Rank: Ordinal Description for Invariant Feature Correspondence

15 years 7 months ago
SIFT-Rank: Ordinal Description for Invariant Feature Correspondence
This paper investigates ordinal image description for invariant feature correspondence. Ordinal description is a meta-technique which considers image measurements in terms of their ranks in a sorted array, instead of the measurement values themselves. Rank-ordering normalizes descriptors in a manner invariant under monotonic deformations of the underlying image measurements, and therefore serves as a simple, non-parametric substitute for ad hoc scaling and thresholding techniques currently used. Ordinal description is particularly well-suited for invariant features, as the high dimensionality of state-of-the-art descriptors permits a large number of unique rank-orderings, and the computationally complex step of sorting is only required once after geometrical normalization. Correspondence trials based on a benchmark data set show that in general, rank-ordered SIFT (SIFT-Rank) descriptors outperform other state-of-the-art descriptors in terms of precisionrecall, includin...
Matthew Toews, William M. Wells III
Added 09 May 2009
Updated 10 Dec 2009
Type Conference
Year 2009
Where CVPR
Authors Matthew Toews, William M. Wells III
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