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SIGMOD
2003
ACM
237views Database» more  SIGMOD 2003»
14 years 9 months ago
Qcluster: Relevance Feedback Using Adaptive Clustering for Content-Based Image Retrieval
The learning-enhanced relevance feedback has been one of the most active research areas in content-based image retrieval in recent years. However, few methods using the relevance ...
Deok-Hwan Kim, Chin-Wan Chung
CVPR
2009
IEEE
15 years 3 months ago
Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
Most modern computer vision systems for high-level tasks, such as image classification, object recognition and segmentation, are based on learning algorithms that are able to se...
Peter V. Gehler, Sebastian Nowozin
CVPR
2005
IEEE
14 years 10 months ago
A Sparse Object Category Model for Efficient Learning and Exhaustive Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
Robert Fergus, Pietro Perona, Andrew Zisserman
MIR
2004
ACM
236views Multimedia» more  MIR 2004»
14 years 2 months ago
Boosting contextual information in content-based image retrieval
We present a new framework for characterizing and retrieving objects in cluttered scenes. This CBIR system is based on a new representation describing every object taking into acc...
Jaume Amores, Nicu Sebe, Petia Radeva, Theo Gevers...
CGF
2006
183views more  CGF 2006»
13 years 8 months ago
Data-driven Local Coordinate Systems for Image-Based Rendering
Image-based representations of an object profit from known geometry. The more accurate this geometry is known, the better corresponding pixels in the different images can be align...
Gero Müller, Ralf Sarlette, Reinhard Klein