PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

SURF: Speeded Up Robust Features
Herbert Bay, Tinne Tuytelaars, Luc Van Gool and Luc Van Gool
In: 9th European Conference on Computer Vision, 7-13 May 2006, Graz, Austria.

Abstract

In this paper, we present a novel scale- and rotation-invariant interest point detector and descriptor, coined SURF (Speeded Up Robust Features). It approximates or even outperforms previously proposed schemes with respect to repeatability, distinctiveness, and robustness, yet can be computed and compared much faster. This is achieved by relying on integral images for image convolutions; by building on the strengths of the leading existing detectors and descriptors (in casu, using a Hessian matrix-based measure for the detector, and a distribution-based descriptor); and by simplifying these methods to the essential. This leads to a combination of novel detection, description, and matching steps. The paper presents experimental results on a standard evaluation set, as well as on imagery obtained in the context of a real-life object recognition application. Both show SURF’s strong performance.

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EPrint Type:Conference or Workshop Item (Poster)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:2183
Deposited By:Tinne Tuytelaars
Deposited On:18 August 2006