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» An Improvement on PCA Algorithm for Face Recognition
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CVPR
2005
IEEE
14 years 9 months ago
Representational Oriented Component Analysis (ROCA) for Face Recognition with One Sample Image per Training Class
Subspace methods such as PCA, LDA, ICA have become a standard tool to perform visual learning and recognition. In this paper we propose Representational Oriented Component Analysi...
Fernando De la Torre, Ralph Gross, Simon Baker, B....
ICIP
2006
IEEE
14 years 9 months ago
Fusion of Visible and Infrared Images using Empirical Mode Decomposition to Improve Face Recognition
In this effort, we propose a new image fusion technique, utilizing Empirical Mode Decomposition (EMD), for improved face recognition. EMD is a non-parametric datadriven analysis t...
Harishwaran Hariharan, Andreas Koschan, Besma R. A...
FGR
2000
IEEE
141views Biometrics» more  FGR 2000»
13 years 11 months ago
Memory-Based Face Recognition for Visitor Identification
We show that a simple, memory-based technique for appearance-based face recognition, motivated by the realworld task of visitor identification, can outperform more sophisticated a...
Terence Sim, Rahul Sukthankar, Matthew D. Mullin, ...
CVPR
2006
IEEE
14 years 9 months ago
Recognize High Resolution Faces: From Macrocosm to Microcosm
Human faces manifest distinct structures and characteristics when observed in different scales. Traditional face recognition techniques mainly rely on low-resolution face images, ...
Dahua Lin, Xiaoou Tang
ICPR
2008
IEEE
14 years 1 months ago
A 2D model for face superresolution
Traditional face superresolution methods treat face images as 1D vectors and apply PCA on the set of these 1D vectors to learn the face subspace. Zhang et al [7] proposed Two-dire...
B. G. Vijay Kumar, Rangarajan Aravind