PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Speeded-up Robust Features (SURF)
Herbert Bay, Andreas Ess, Tinne Tuytelaars, Luc Van Gool and Luc Van Gool
Computer Vision and Image Understanding (CVIU) 2007.

Abstract

This article presents a novel scale- and rotation-invariant detector and descriptor, coined SURF (Speeded-Up Robust Features). SURF 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 (specifically, 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 encompasses a detailed description of the detector and descriptor and then explores the effect of the most important parameters. We conclude the article with SURF’s application to two challenging, yet converse goals: camera calibration as a special case of image registration,

EPrint Type:Article
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Machine Vision
ID Code:3637
Deposited By:Luc Van Gool
Deposited On:14 February 2008