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ICCV
2011
IEEE
12 years 5 months ago
Informative Feature Selection for Object Recognition via Sparse PCA
Bag-of-words (BoW) methods are a popular class of object recognition methods that use image features (e.g., SIFT) to form visual dictionaries and subsequent histogram vectors to r...
Nikhil Naikal, Allen Y. Yang, S. Shankar Sastry
CVPR
2008
IEEE
14 years 7 months ago
Unsupervised feature selection via distributed coding for multi-view object recognition
Object recognition accuracy can be improved when information from multiple views is integrated, but information in each view can often be highly redundant. We consider the problem...
Chris Mario Christoudias, Raquel Urtasun, Trevor D...
IJCV
2008
241views more  IJCV 2008»
13 years 5 months ago
Object Class Recognition and Localization Using Sparse Features with Limited Receptive Fields
We investigate the role of sparsity and localized features in a biologically-inspired model of visual object classification. As in the model of Serre, Wolf, and Poggio, we first a...
Jim Mutch, David G. Lowe
CVPR
2006
IEEE
14 years 7 months ago
Multiclass Object Recognition with Sparse, Localized Features
We apply a biologically inspired model of visual object recognition to the multiclass object categorization problem. Our model modifies that of Serre, Wolf, and Poggio. As in that...
Jim Mutch, David G. Lowe
ICCV
2011
IEEE
12 years 5 months ago
Sparse Dictionary-based Representation and Recognition of Action Attributes
We present an approach for dictionary learning of action attributes via information maximization. We unify the class distribution and appearance information into an objective func...
Qiang Qiu, Zhuolin Jiang, Rama Chellappa