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BMVC
2000
13 years 8 months ago
Probabilistic PCA and ICA Subspace Mixture Models for Image Segmentation
High-dimensional data, such as images represented as points in the space spanned by their pixel values, can often be described in a significantly smaller number of dimensions than...
Dick de Ridder, Josef Kittler, Robert P. W. Duin
CVPR
2004
IEEE
13 years 11 months ago
Face Localization via Hierarchical CONDENSATION with Fisher Boosting Feature Selection
We formulate face localization as a Maximum A Posteriori Probability(MAP) problem of finding the best estimation of human face configuration in a given image. The a prior distribu...
Jilin Tu, ZhenQiu Zhang, Zhihong Zeng, Thomas S. H...
ICIP
2008
IEEE
14 years 9 months ago
Principal components for non-local means image denoising
This paper presents an image denoising algorithm that uses principal component analysis (PCA) in conjunction with the non-local means image denoising. Image neighborhood vectors u...
Tolga Tasdizen
CVPR
2007
IEEE
14 years 9 months ago
Discriminant Mutual Subspace Learning for Indoor and Outdoor Face Recognition
Outdoor face recognition is among the most challenging problems for face recognition. In this paper, we develop a discriminant mutual subspace learning algorithm for indoor and ou...
Zhifeng Li, Dahua Lin, Helen M. Meng, Xiaoou Tang
ACCV
2007
Springer
14 years 1 months ago
Kernel Discriminant Analysis Based on Canonical Differences for Face Recognition in Image Sets
A novel kernel discriminant transformation (KDT) algorithm based on the concept of canonical differences is presented for automatic face recognition applications. For each individu...
Wen-Sheng Vincent Chu, Ju-Chin Chen, Jenn-Jier Jam...