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» Learning Models for Object Recognition
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DAGM
2008
Springer
13 years 10 months ago
Boosting for Model-Based Data Clustering
In this paper a novel and generic approach for model-based data clustering in a boosting framework is presented. This method uses the forward stagewise additive modeling to learn t...
Amir Saffari, Horst Bischof
ACCV
2007
Springer
14 years 3 months ago
Hierarchical Learning of Dominant Constellations for Object Class Recognition
Abstract. The importance of spatial configuration information for object class recognition is widely recognized. Single isolated local appearance codes are often ambiguous. On the...
Nathan Mekuz, John K. Tsotsos
CVPR
2005
IEEE
14 years 2 months ago
Jensen-Shannon Boosting Learning for Object Recognition
In this paper, we propose a novel learning method, called Jensen-Shannon Boosting (JSBoost) and demonstrate its application to object recognition. JSBoost incorporates Jensen-Shan...
Xiangsheng Huang, Stan Z. Li, Yangsheng Wang
CVPR
2006
IEEE
14 years 3 months ago
Towards Multi-View Object Class Detection
We present a novel system for generic object class detection. In contrast to most existing systems which focus on a single viewpoint or aspect, our approach can detect object inst...
Alexander Thomas, Vittorio Ferrari, Bastian Leibe,...
ICCV
2009
IEEE
15 years 2 months ago
Seeing 3D Objects in a Single 2D Image
A general framework simultaneously addressing pose estimation, 2D segmentation, object recognition, and 3D reconstruction from a single image is introduced in this paper. The pr...
Diego Rother, Guillermo Sapiro