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» Boosting Object Detection Using Feature Selection
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CVPR
2005
IEEE
15 years 10 months ago
The Distinctiveness, Detectability, and Robustness of Local Image Features
We introduce a new method that characterizes typical local image features (e.g., SIFT [9], phase feature [3]) in terms of their distinctiveness, detectability, and robustness to i...
Gustavo Carneiro, Allan D. Jepson
CVPR
2008
IEEE
16 years 6 months ago
Scale invariance without scale selection
In this work we construct scale invariant descriptors (SIDs) without requiring the estimation of image scale; we thereby avoid scale selection which is often unreliable. Our start...
Iasonas Kokkinos, Alan L. Yuille
ICASSP
2011
IEEE
14 years 8 months ago
Objective evaluation of the Dynamic Model Selection method for spectral voice conversion
Spectral voice conversion is usually performed using a single model selected in order to represent a tradeoff between goodness of fit and complexity. Recently, we proposed a new ...
Pierre Lanchantin, Xavier Rodet
SMC
2010
IEEE
132views Control Systems» more  SMC 2010»
15 years 3 months ago
Selection of SIFT feature points for scene description in robot vision
This paper presents a method for selection of SIFT(Scale-Invariant Feature Transform) feature points using OC-SVM (One Class-Support Vector Machines). We proposed the method for au...
Yuya Utsumi, Masahiro Tsukada, Hirokazu Madokoro, ...
CVPR
2007
IEEE
16 years 6 months ago
Toward A Discriminative Codebook: Codeword Selection across Multi-resolution
In patch-based object recognition, there are two important issues on the codebook generation: (1) resolution: a coarse codebook lacks sufficient discriminative power, and an over-...
Lei Wang