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IJCV
2008
241views more  IJCV 2008»
13 years 8 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 10 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
PAMI
2012
11 years 11 months ago
Trainable Convolution Filters and Their Application to Face Recognition
—In this paper, we present a novel image classification system that is built around a core of trainable filter ensembles that we call Volterra kernel classifiers. Our system trea...
Ritwik Kumar, Arunava Banerjee, Baba C. Vemuri, Ha...
TIM
2011
172views more  TIM 2011»
13 years 3 months ago
Selecting a Reference High Resolution for Fingerprint Recognition Using Minutiae and Pores
—High-resolution automated fingerprint recognition systems (AFRSs) offer higher security because they are able to make use of level-3 features, such as pores, that are not avail...
David Zhang, Feng Liu, Qijun Zhao, Guangming Lu, N...
ICPR
2010
IEEE
13 years 6 months ago
3D Face Decomposition and Region Selection Against Expression Variations
3D face recognition exploits shape information as well as texture information in 2D systems. The use of whole 3D face is sensitive to some undesired situations like expression var...
Göksel Günlü, Hasan S. Bilge