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CIVR
2003
Springer
133views Image Analysis» more  CIVR 2003»
14 years 1 months ago
A Closer Look at Boosted Image Retrieval
Margin-maximizing techniques such as boosting have been generating excitement in machine learning circles for several years now. Although these techniques offer significant impro...
Nicholas R. Howe
ICCV
2009
IEEE
15 years 28 days ago
Ground truth dataset and baseline evaluations for intrinsic image algorithms
The intrinsic image decomposition aims to retrieve “intrinsic” properties of an image, such as shading and reflectance. To make it possible to quantitatively compare differe...
Roger Grosse, Micah K. Johnson, Edward H. Adelson,...
CVPR
2006
IEEE
14 years 10 months ago
A Simple Bayesian Framework for Content-Based Image Retrieval
We present a Bayesian framework for content-based image retrieval which models the distribution of color and texture features within sets of related images. Given a userspecified ...
Katherine A. Heller, Zoubin Ghahramani
ICIP
2007
IEEE
14 years 9 months ago
Do Colour Interest Points Improve Image Retrieval?
In image retrieval scenarios, many methods use interest point detection at an early stage to find regions in which descriptors are calculated. Finding salient locations in image d...
Allan Hanbury, Julian Stöttinger, Nicu Sebe, ...
ICMCS
2000
IEEE
137views Multimedia» more  ICMCS 2000»
14 years 11 days ago
Automatic Query Generation for Content-Based Image Retrieval
We describe a subsystem of a content-based image retrieval (CBIR) environment that supports a user in the definition of image similarity. Out of a single image or a set of query i...
Christian Breiteneder, Horst Eidenberger