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» Linear Regression for Face Recognition
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ECCV
2010
Springer
14 years 9 months ago
Coupled Gaussian Process Regression for Pose-Invariant Facial Expression Recognition
We present a novel framework for the recognition of facial expressions at arbitrary poses that is based on 2D geometric features. We address the problem by first mapping the 2D loc...
Ognjen Rudovic, Ioannis Patras, Maja Pantic
ICIP
2002
IEEE
16 years 1 months ago
A kernel machine based approach for multi-view face recognition
Techniques that can introduce low-dimensional feature representation with enhanced discriminatory power is of paramount importance in face recognition applications. It is well kno...
Juwei Lu, Kostas N. Plataniotis, Anastasios N. Ven...
SCIA
2007
Springer
122views Image Analysis» more  SCIA 2007»
15 years 5 months ago
Individual Discriminative Face Recognition Models Based on Subsets of Features
Abstract. The accuracy of data classification methods depends considerably on the data representation and on the selected features. In this work, the elastic net model selection i...
Line Harder Clemmensen, David Delgado Gomez, Bjarn...
ICPR
2010
IEEE
15 years 6 months ago
Heterogeneous Face Recognition: Matching NIR to Visible Light Images
Matching near-infrared (NIR) face images to visible light (VIS) face images offers a robust approach to face recognition with unconstrained illumination. In this paper we propose ...
Brendan Klare, Anil Jain
TIFS
2008
157views more  TIFS 2008»
14 years 11 months 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, ...