84 search results - page 1 / 17 » Robust Matrix Decomposition with Outliers |
CORR
2010
Springer
13 years 4 months ago
2010
Springer
Suppose a given observation matrix can be decomposed as the sum of a low-rank matrix and a sparse matrix (outliers), and the goal is to recover these individual components from th...
CORR
2010
Springer
13 years 3 months ago
2010
Springer
Singular Value Decomposition (and Principal Component Analysis) is one of the most widely used techniques for dimensionality reduction: successful and efficiently computable, it ...
CVPR
2005
IEEE
14 years 6 months ago
2005
IEEE
Matrix factorization has many applications in computer vision. Singular Value Decomposition (SVD) is the standard algorithm for factorization. When there are outliers and missing ...
CVPR
2000
IEEE
14 years 6 months ago
2000
IEEE
A novel algorithm for motion segmentation is proposed. The algorithm uses the fact that shape of an object with homogeneous motion is represented as 4 dimensional linear space. Th...
CVPR
2010
IEEE
13 years 2 months ago
2010
IEEE
The calculation of a low-rank approximation of a matrix is a fundamental operation in many computer vision applications. The workhorse of this class of problems has long been the ...