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» Boosting linear discriminant analysis for face recognition
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JMM2
2006
149views more  JMM2 2006»
13 years 7 months ago
Invariant Robust 3-D Face Recognition based on the Hilbert Transform in Spectral Space
One of the main objectives of face recognition is to determine whether an acquired face belongs to a reference database and to subsequently identify the corresponding individual. F...
Eric Paquet, Marc Rioux
MCS
2007
Springer
14 years 1 months ago
An Experimental Study on Rotation Forest Ensembles
Rotation Forest is a recently proposed method for building classifier ensembles using independently trained decision trees. It was found to be more accurate than bagging, AdaBoost...
Ludmila I. Kuncheva, Juan José Rodrí...
PR
2007
137views more  PR 2007»
13 years 7 months ago
Boosted manifold principal angles for image set-based recognition
In this paper we address the problem of classifying vector sets. We motivate and introduce a novel method based on comparisons between corresponding vector subspaces. In particula...
Tae-Kyun Kim, Ognjen Arandjelovic, Roberto Cipolla
IVC
2006
175views more  IVC 2006»
13 years 7 months ago
Face recognition using optimal linear components of range images
This paper investigates the use of range images of faces for recognizing people. 3D scans of faces lead to range images that are linearly projected to low-dimensional subspaces fo...
Anuj Srivastava, Xiuwen Liu, Curt Hesher
PAMI
2008
153views more  PAMI 2008»
13 years 7 months ago
Correlation Metric for Generalized Feature Extraction
Beyond conventional linear and kernel-based feature extraction, we present a more generalized formulation for feature extraction in this paper. Two representative algorithms using ...
Yun Fu, Shuicheng Yan, Thomas S. Huang