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146
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TIFS
2008
157views more  TIFS 2008»
15 years 22 days ago
Subspace Approximation of Face Recognition Algorithms: An Empirical Study
We present a theory for constructing linear subspace approximations to face-recognition algorithms and empirically demonstrate that a surprisingly diverse set of face-recognition a...
Pranab Mohanty, Sudeep Sarkar, Rangachar Kasturi, ...
135
Voted
KDD
2012
ACM
183views Data Mining» more  KDD 2012»
13 years 3 months ago
Mining discriminative components with low-rank and sparsity constraints for face recognition
This paper introduces a novel image decomposition approach for an ensemble of correlated images, using low-rank and sparsity constraints. Each image is decomposed as a combination...
Qiang Zhang, Baoxin Li
83
Voted
ICPR
2004
IEEE
16 years 1 months ago
Face Recognition Based on Discriminative Manifold Learning
In this paper, a discriminative manifold learning method for face recognition is proposed which achieved the discriminative embedding the high dimensional face data into a low dim...
Kap Luk Chan, Lei Wang, Yiming Wu
106
Voted
AVSS
2006
IEEE
15 years 6 months ago
Feature Modelling of PCA Difference Vectors for 2D and 3D Face Recognition
This paper examines the the effectiveness of feature modelling to conduct 2D and 3D face recognition. In particular, PCA difference vectors are modelled using Gaussian Mixture Mod...
Chris McCool, Jamie Cook, Vinod Chandran, Sridha S...
131
Voted
CRV
2005
IEEE
132views Robotics» more  CRV 2005»
15 years 6 months ago
Face Recognition with Weighted Locally Linear Embedding
We present an approach to recognizing faces with varying appearances which also considers the relative probability of occurrence for each appearance. We propose and demonstrate ex...
Nathan Mekuz, Christian Bauckhage, John K. Tsotsos