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» The Global Dimensionality of Face Space
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CVPR
2006
IEEE
14 years 10 months ago
Dimensionality Reduction by Learning an Invariant Mapping
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
Raia Hadsell, Sumit Chopra, Yann LeCun
IJBC
2008
85views more  IJBC 2008»
13 years 8 months ago
Center bifurcation for Two-Dimensional Border-Collision Normal Form
In this work we study some properties associated with the bordercollision bifurcations in a two-dimensional piecewise linear map in canonical form, related to the case in which a ...
Iryna Sushko, Laura Gardini
TSMC
2008
182views more  TSMC 2008»
13 years 7 months ago
Incremental Linear Discriminant Analysis for Face Recognition
Abstract--Dimensionality reduction methods have been successfully employed for face recognition. Among the various dimensionality reduction algorithms, linear (Fisher) discriminant...
Haitao Zhao, Pong Chi Yuen
ICIP
2008
IEEE
14 years 10 months ago
On the estimation of geodesic paths on sampled manifolds under random projections
In this paper, we focus on the use of random projections as a dimensionality reduction tool for sampled manifolds in highdimensional Euclidean spaces. We show that geodesic paths ...
Mona Mahmoudi, Pierre Vandergheynst, Matteo Sorci
WACV
2008
IEEE
14 years 2 months ago
Mosaicfaces: a discrete representation for face recognition
Most face recognition algorithms use a “distancebased” approach: gallery and probe images are projected into a low dimensional feature space and decisions about matching are b...
Jania Aghajanian, Simon J. D. Prince