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» On SIFTs and their scales
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ICCV
2005
IEEE
14 years 11 months ago
Local Features for Object Class Recognition
In this paper we compare the performance of local detectors and descriptors in the context of object class recognition. Recently, many detectors / descriptors have been evaluated ...
Krystian Mikolajczyk, Bastian Leibe, Bernt Schiele
ICRA
2005
IEEE
138views Robotics» more  ICRA 2005»
14 years 3 months ago
Urban Object Recognition from Informative Local Features
Abstract— Autonomous mobile agents require object recognition for high level interpretation and localization in complex scenes. In urban environments, recognition of buildings mi...
Gerald Fritz, Christin Seifert, Lucas Paletta
CVPR
2012
IEEE
12 years 7 days ago
Three things everyone should know to improve object retrieval
The objective of this work is object retrieval in large scale image datasets, where the object is specified by an image query and retrieval should be immediate at run time in the...
Relja Arandjelovic, Andrew Zisserman
CVPR
2012
IEEE
12 years 7 days ago
D-Nets: Beyond patch-based image descriptors
Despite much research on patch-based descriptors, SIFT remains the gold standard for finding correspondences across images and recent descriptors focus primarily on improving spe...
Felix von Hundelshausen, Rahul Sukthankar
ICIP
2008
IEEE
14 years 11 months ago
Using point correspondences without projective deformation for multi-view stereo reconstruction
This paper proposes a novel algorithm to reconstruct a 3D surface from a calibrated set of images. In a first pass, it uses Scale Invariant Features Transform (SIFT) descriptor co...
Adrien Auclair, Nicole Vincent, Laurent D. Cohen