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» Mercer Kernels for Object Recognition with Local Features
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CVPR
2005
IEEE
14 years 6 months ago
Mercer Kernels for Object Recognition with Local Features
A new class of kernels for object recognition based on local image feature representations are introduced in this paper. These kernels satisfy the Mercer condition and incorporate...
Siwei Lyu
ICCV
2003
IEEE
14 years 6 months ago
Recognition with Local Features: the Kernel Recipe
Recent developments in computer vision have shown that local features can provide efficient representations suitable for robust object recognition. Support Vector Machines have be...
Christian Wallraven, Barbara Caputo, Arnulf B. A. ...
ICCV
2007
IEEE
14 years 6 months ago
Proximity Distribution Kernels for Geometric Context in Category Recognition
We propose using the proximity distribution of vectorquantized local feature descriptors for object and category recognition. To this end, we introduce a novel "proximity dis...
Haibin Ling, Stefano Soatto
ICML
2008
IEEE
14 years 5 months ago
Robust matching and recognition using context-dependent kernels
The success of kernel methods including support vector machines (SVMs) strongly depends on the design of appropriate kernels. While initially kernels were designed in order to han...
Hichem Sahbi, Jean-Yves Audibert, Jaonary Rabariso...
ICPR
2004
IEEE
14 years 5 months ago
Object Categorization via Local Kernels
In this paper we consider the problem of multi-object categorization. We present an algorithm that combines support vector machines with local features via a new class of Mercer k...
Barbara Caputo, Christian Wallraven, Maria-Elena N...