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ICPR
2004
IEEE

Object Categorization via Local Kernels

9 years 6 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 kernels. This class of kernels allows us to perform scalar products on feature vectors consisting of local descriptors, computed around interest points (like corners); these feature vectors are generally of different lengths for different images. The resulting framework is able to recognize multi-object categories in different settings, from lab-controlled to real-world scenes. We present several experiments, on different databases, and we benchmark our results with state-of-the-art algorithms for categorization, achieving excellent results.
Barbara Caputo, Christian Wallraven, Maria-Elena N
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2004
Where ICPR
Authors Barbara Caputo, Christian Wallraven, Maria-Elena Nilsback
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