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» Feature Hierarchies for Object Classification
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CVPR
2008
IEEE
14 years 9 months ago
Unsupervised learning of probabilistic object models (POMs) for object classification, segmentation and recognition
We present a new unsupervised method to learn unified probabilistic object models (POMs) which can be applied to classification, segmentation, and recognition. We formulate this a...
Yuanhao Chen, Long Zhu, Alan L. Yuille, HongJiang ...
CVPR
2006
IEEE
14 years 9 months ago
A Design Principle for Coarse-to-Fine Classification
Coarse-to-fine classification is an efficient way of organizing object recognition in order to accommodate a large number of possible hypotheses and to systematically exploit shar...
Sachin Gangaputra, Donald Geman
CVPR
2005
IEEE
14 years 9 months ago
Part-Based Statistical Models for Object Classification and Detection
We propose using simple mixture models to define a set of mid-level binary local features based on binary oriented edge input. The features capture natural local structures in the...
Elliot Joel Bernstein, Yali Amit
ICPR
2008
IEEE
14 years 8 months ago
Multiple view based 3D object classification using ensemble learning of local subspaces
Multiple observation improves the performance of 3D object classification. However, since the distribution of feature vectors obtained from multiple view points have strong nonlin...
Jianing Wu, Kazuhiro Fukui
CIVR
2008
Springer
227views Image Analysis» more  CIVR 2008»
13 years 9 months ago
A comparison of color features for visual concept classification
Concept classification is important to access visual information on the level of objects and scene types. So far, intensity-based features have been widely used. To increase discr...
Koen E. A. van de Sande, Theo Gevers, Cees G. M. S...