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CVPR
2005
IEEE
14 years 7 months ago
Robust L1 Norm Factorization in the Presence of Outliers and Missing Data by Alternative Convex Programming
Matrix factorization has many applications in computer vision. Singular Value Decomposition (SVD) is the standard algorithm for factorization. When there are outliers and missing ...
Qifa Ke, Takeo Kanade
ICASSP
2011
IEEE
12 years 9 months ago
Robust talking face video verification using joint factor analysis and sparse representation on GMM mean shifted supervectors
It has been previously demonstrated that systems based on block wise local features and Gaussian mixture models (GMM) are suitable for video based talking face verification due t...
Ming Li, Shrikanth Narayanan
CSDA
2010
157views more  CSDA 2010»
13 years 5 months ago
Robust estimation of constrained covariance matrices for confirmatory factor analysis
Confirmatory factor analysis (CFA) is a data anylsis procedure that is widely used in social and behavioral sciences in general and other applied sciences that deal with large qua...
E. Dupuis Lozeron, M. P. Victoria-Feser
3DPVT
2006
IEEE
236views Visualization» more  3DPVT 2006»
13 years 12 months ago
Multiple Camera Calibration Using Robust Perspective Factorization
In this paper we address the problem of recovering structure and motion from a large number of intrinsically calibrated perspective cameras. We describe a method that combines (1)...
Andrei Zaharescu, Radu Horaud, Rémi Ronfard...
ICML
2006
IEEE
14 years 6 months ago
R1-PCA: rotational invariant L1-norm principal component analysis for robust subspace factorization
Principal component analysis (PCA) minimizes the sum of squared errors (L2-norm) and is sensitive to the presence of outliers. We propose a rotational invariant L1-norm PCA (R1-PC...
Chris H. Q. Ding, Ding Zhou, Xiaofeng He, Hongyuan...