CVPR
2010
IEEE
13 years 5 months ago
2010
IEEE
This paper addresses the problem of segmenting a combination of linear subspaces and quadratic surfaces from sample data points corrupted by (not necessarily small) noise. Our mai...
NIPS
2004
13 years 6 months ago
2004
Recently, there have been several advances in the machine learning and pattern recognition communities for developing manifold learning algorithms to construct nonlinear low-dimen...
ECCV
2002
Springer
14 years 7 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 7 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...