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AMFG
2005
IEEE
203views Biometrics» more  AMFG 2005»
15 years 6 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
116
Voted
ECCV
2006
Springer
16 years 2 months ago
Face Recognition from Video Using the Generic Shape-Illumination Manifold
Abstract. In spite of over two decades of intense research, illumination and pose invariance remain prohibitively challenging aspects of face recognition for most practical applica...
Ognjen Arandjelovic, Roberto Cipolla
100
Voted
CVPR
2007
IEEE
16 years 2 months ago
Face Recognition using Discriminatively Trained Orthogonal Rank One Tensor Projections
We propose a method for face recognition based on a discriminative linear projection. In this formulation images are treated as tensors, rather than the more conventional vector o...
Gang Hua, Paul A. Viola, Steven M. Drucker
110
Voted
ECCV
1994
Springer
16 years 2 months ago
Face Recognition: the Problem of Compensating for Changes in Illumination Direction
A face recognition system must recognize a face from a novel image despite the variations between images of the same face. A common approach to overcoming image variations because...
Yael Moses, Yael Adini, Shimon Ullman
109
Voted
ICPR
2004
IEEE
16 years 1 months ago
Bayesian Face Recognition Based on Gaussian Mixture Models
Bayesian analysis is a popular subspace based face recognition method. It casts the face recognition task into a binary classification problem with each of the two classes, intrap...
Xiaogang Wang, Xiaoou Tang