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» Improved SIFT-Features Matching for Object Recognition
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CVPR
2009
IEEE
15 years 2 months ago
Unsupervised Learning for Graph Matching
Graph matching is an important problem in computer vision. It is used in 2D and 3D object matching and recognition. Despite its importance, there is little literature on learnin...
Marius Leordeanu, Martial Hebert
ICCV
2005
IEEE
14 years 1 months ago
Non-Negative Lighting and Specular Object Recognition
Recognition of specular objects is particularly difficult because their appearance is much more sensitive to lighting changes than that of Lambertian objects. We consider an appr...
Sameer Shirdhonkar, David W. Jacobs
CVPR
2009
IEEE
14 years 2 months ago
Disambiguating the recognition of 3D objects
We propose novel algorithms for the detection, segmentation, recognition, and pose estimation of threedimensional objects. Our approach initially infers geometric primitives to de...
Gutemberg Guerra-Filho
ICCV
2005
IEEE
14 years 9 months ago
Local Features for Object Class Recognition
In this paper we compare the performance of local detectors and descriptors in the context of object class recognition. Recently, many detectors / descriptors have been evaluated ...
Krystian Mikolajczyk, Bastian Leibe, Bernt Schiele
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
13 years 9 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang