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ECCV
2000
Springer
14 years 9 months ago
Unsupervised Learning of Models for Recognition
We present a method to learn object class models from unlabeled and unsegmented cluttered scenes for the purpose of visual object recognition. We focus on a particular type of mode...
Markus Weber, Max Welling, Pietro Perona
DICTA
2009
13 years 8 months ago
Modeling Image Context Using Object Centered Grid
Abstract--Context plays a valuable role in any image understanding task confirmed by numerous studies which have shown the importance of contextual information in computer vision t...
Sobhan Naderi Parizi, Ivan Laptev, Alireza Tavakol...
ISBI
2008
IEEE
14 years 8 months ago
Statistical colocalization in biological imaging with false discovery control
In this paper, we present a novel object-based statistical colocalization method. Our colocalization relies on multiple hypothesis tests on the distances between all pairs of the ...
Bo Zhang, Nicolas Chenouard, Jean-Christophe Olivo...
ICASSP
2011
IEEE
12 years 11 months ago
Combining generic and class-specific codebooks for object categorization and detection
Combining advantages of shape and appearance features, we propose a novel model that integrates these two complementary features into a common framework for object categorization ...
Hong Pan, Yaping Zhu, Liang-Zheng Xia, Truong Q. N...
IJCV
2000
164views more  IJCV 2000»
13 years 7 months ago
Probabilistic Modeling and Recognition of 3-D Objects
This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...
Joachim Hornegger, Heinrich Niemann