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» The Global Dimensionality of Face Space
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CVPR
2006
IEEE
16 years 8 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»
15 years 6 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»
15 years 6 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
16 years 8 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
16 years 1 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