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» Spiders as Robust Point Descriptors
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BMVC
2002
13 years 10 months ago
Invariant Features from Interest Point Groups
This paper approaches the problem of finding correspondences between images in which there are large changes in viewpoint, scale and illumination. Recent work has shown that scale...
Matthew Brown, David G. Lowe
ACIVS
2008
Springer
14 years 2 months ago
Robust Curvature Extrema Detection Based on New Numerical Derivation
Abstract. Extrema of curvature are useful key points for different image analysis tasks. Indeed, polygonal approximation or arc decomposition methods used often these points to ini...
Cédric Join, Salvatore Tabbone
ICCV
2001
IEEE
14 years 9 months ago
Indexing Based on Scale Invariant Interest Points
This paper presents a new method for detecting scale invariant interest points. The method is based on two recent results on scale space: 1) Interest points can be adapted to scal...
Krystian Mikolajczyk, Cordelia Schmid
CVPR
2010
IEEE
13 years 12 months ago
Model Globally, Match Locally: Efficient and Robust 3D Object Recognition
This paper addresses the problem of recognizing freeform 3D objects in point clouds. Compared to traditional approaches based on point descriptors, which depend on local informati...
Bertram Drost, Markus Ulrich, Nassir Navab, Slobod...
ECCV
2006
Springer
14 years 9 months ago
SURF: Speeded Up Robust Features
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 outperform...
Herbert Bay, Tinne Tuytelaars, Luc J. Van Gool