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» Novel image feature alphabets for object recognition
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CVPR
2005
IEEE
14 years 10 months ago
Efficient Image Matching with Distributions of Local Invariant Features
Sets of local features that are invariant to common image transformations are an effective representation to use when comparing images; current methods typically judge feature set...
Kristen Grauman, Trevor Darrell
GECCO
2003
Springer
126views Optimization» more  GECCO 2003»
14 years 1 months ago
Coevolution and Linear Genetic Programming for Visual Learning
In this paper, a novel genetically-inspired visual learning method is proposed. Given the training images, this general approach induces a sophisticated feature-based recognition s...
Krzysztof Krawiec, Bir Bhanu
CVPR
2005
IEEE
14 years 10 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
CVPR
2008
IEEE
14 years 10 months ago
Recognition by association via learning per-exemplar distances
We pose the recognition problem as data association. In this setting, a novel object is explained solely in terms of a small set of exemplar objects to which it is visually simila...
Tomasz Malisiewicz, Alexei A. Efros
CVPR
2001
IEEE
14 years 10 months ago
Local Feature View Clustering for 3D Object Recognition
There have been important recent advances in object recognition through the matching of invariant local image features. However, the existing approaches are based on matching to i...
David G. Lowe