Research

Multi-Scale Oriented Patches


Reference:

Brown, M., Szeliski, R. and Winder, S., 2004. Multi-Scale Oriented Patches. Other. Microsoft Research.

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Official URL:

http://research.microsoft.com/apps/pubs/default.aspx?id=70120

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Abstract

This paper describes a novel multi-view matching framework based on a new type of invariant feature. Our features are located at Harris corners in discrete scale-space and oriented using a blurred local gradient. This defines a rotationally invariant frame in which we sample a feature descriptor, which consists of an 8x8 patch of bias/gain normalised intensity values. The density of features in the image is controlled using a novel adaptive non-maximal suppression algorithm, which gives a better spatial distribution of features than previous approaches. Matching is achieved using a fast nearest neighbour algorithm that indexes features based on their low frequency Haar wavelet coefficients. We also introduce a novel outlier rejection procedure that verifies a pairwise feature match based on a background distribution of incorrect feature matches. Feature matches are refined using RANSAC and used in an automatic 2D panorama stitcher that has been extensively tested on hundreds of sample inputs.

Details

Item Type Reports/Papers (Other)
CreatorsBrown, M., Szeliski, R. and Winder, S.
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URLURL Type
http://research.microsoft.com/pubs/70120/tr-2004-133.pdfFree Full-text
DepartmentsFaculty of Science > Computer Science
StatusPublished
ID Code26125
Additional InformationID number: MSR-TR-2004-133

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