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» Discriminant Embedding for Local Image Descriptors
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ICCV
2011
IEEE
12 years 9 months ago
Local Intensity Order Pattern for Feature Description
This paper presents a novel method for feature description based on intensity order. Specifically, a Local Intensity Order Pattern(LIOP) is proposed to encode the local ordinal i...
Zhenhua Wang, Bin Fan, Fuchao Wu
SGP
2007
13 years 11 months ago
Laplace-Beltrami eigenfunctions for deformation invariant shape representation
A deformation invariant representation of surfaces, the GPS embedding, is introduced using the eigenvalues and eigenfunctions of the Laplace-Beltrami differential operator. Notabl...
Raif M. Rustamov
ECCV
2008
Springer
14 years 11 months ago
Weakly Supervised Object Localization with Stable Segmentations
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
CVPR
2005
IEEE
14 years 11 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
BMVC
2002
13 years 11 months ago
Invariant Features from Interest Point Groups
This paper approaches the problem of finding correspondences between images in which there are large changes in viewpoint, scale and illumination. Recent work has shown that scale...
Matthew Brown, David G. Lowe