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» Feature Modelling of PCA Difference Vectors for 2D and 3D Fa...
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AVSS
2006
IEEE
12 years 7 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...
AC
2003
Springer
12 years 5 months ago
Influence of Location over Several Classifiers in 2D and 3D Face Verification
In this paper two methods for human face recognition and the influence of location mistakes are shown. First one, Principal Components Analysis (PCA), has been one of the most appl...
Susana Mata, Cristina Conde, Araceli Sánche...
AMFG
2005
IEEE
203views Biometrics» more  AMFG 2005»
12 years 7 months ago
Learning to Fuse 3D+2D Based Face Recognition at Both Feature and Decision Levels
2D intensity images and 3D shape models are both useful for face recognition, but in different ways. While algorithms have long been developed using 2D or 3D data, recently has see...
Stan Z. Li, ChunShui Zhao, Meng Ao, Zhen Lei
ICMCS
2007
IEEE
279views Multimedia» more  ICMCS 2007»
12 years 8 months ago
Geodesic Distances for 3D-3D and 2D-3D Face Recognition
In this paper, we propose an original framework for representing 2D and 3D face information using geodesic distances. This aims to define a representation enabling the direct com...
Stefano Berretti, Alberto Del Bimbo, Pietro Pala, ...
ICMCS
2006
IEEE
311views Multimedia» more  ICMCS 2006»
12 years 7 months ago
Disparity-Based 3D Face Modeling using 3D Deformable Facial Mask for 3D Face Recognition
We present an automatic disparity-based approach for 3D face modeling, from two frontal and one profile view stereo images, for 3D face recognition applications. Once the images a...
A-Nasser Ansari, Mohamed Abdel-Mottaleb, Mohammad ...
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