1088 search results - page 5 / 218 » Robust Principal Component Analysis for Computer Vision |
ECCV
2002
Springer
14 years 9 months ago
2002
Springer
Abstract. Principal Component Analysis (PCA) is one of the most popular techniques for dimensionality reduction of multivariate data points with application areas covering many bra...
CVPR
2003
IEEE
14 years 9 months ago
2003
IEEE
This paper presents an algebro-geometric solution to the problem of segmenting an unknown number of subspaces of unknown and varying dimensions from sample data points. We represen...
TNN
2008
13 years 7 months ago
2008
This paper introduces a multilinear principal component analysis (MPCA) framework for tensor object feature extraction. Objects of interest in many computer vision and pattern rec...
ICCV
2011
IEEE
12 years 7 months ago
2011
IEEE
We propose a novel localized principal component analysis (PCA) based curve evolution approach which evolves the segmenting curve semi-locally within various target regions (divis...
PAMI
2008
13 years 7 months ago
2008
In data-analysis problems with a large number of dimension, principal component analysis based on L2-norm (L2PCA) is one of the most popular methods, but L2-PCA is sensitive to out...