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» Robust Principal Component Analysis for Computer Vision
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CVPR
2009
IEEE
15 years 2 months ago
Multiple View Image Denoising
We present a novel multi-view denoising algorithm. Our algorithm takes noisy images taken from different viewpoints as input and groups similar patches in the input images using ...
Hailin Jin, Li Zhang, Shree K. Nayar, Sundeep Vadd...
ICPR
2010
IEEE
13 years 9 months ago
SemiCCA: Efficient Semi-Supervised Learning of Canonical Correlations
Canonical correlation analysis (CCA) is a powerful tool for analyzing multi-dimensional paired data. However, CCA tends to perform poorly when the number of paired samples is limit...
Akisato Kimura, Hirokazu Kameoka, Masashi Sugiyama...
ICCV
2003
IEEE
14 years 9 months ago
Recognizing Human Action Efforts: An Adaptive Three-Mode PCA Framework
We present a computational framework capable of labeling the effort of an action corresponding to the perceived level of exertion by the performer (low ? high). The approach initi...
James W. Davis, Hui Gao
MICCAI
2008
Springer
14 years 8 months ago
A Novel Explicit 2D+t Cyclic Shape Model Applied to Echocardiography
In this paper, we propose a novel explicit 2D+t cyclic shape model that extends the Point Distribution Model (PDM) to shapes like myocardial contours with cyclic dynamics. We also ...
Ramón Casero, J. Alison Noble
CSDA
2008
158views more  CSDA 2008»
13 years 7 months ago
Outlier identification in high dimensions
A computationally fast procedure for identifying outliers is presented, that is particularly effective in high dimensions. This algorithm utilizes simple properties of principal c...
Peter Filzmoser, Ricardo A. Maronna, Mark Werner