140 search results - page 12 / 28 » Dimensionality Reduction with Adaptive Kernels |
ICML
2004
IEEE
14 years 8 months ago
2004
IEEE
Principal component analysis (PCA) is a widely used statistical technique for unsupervised dimension reduction. K-means clustering is a commonly used data clustering for unsupervi...
ECCV
2006
Springer
14 years 9 months ago
2006
Springer
Many linear discriminant analysis (LDA) and kernel Fisher discriminant analysis (KFD) methods are based on the restrictive assumption that the data are homoscedastic. In this paper...
ICCV
2011
IEEE
12 years 7 months ago
2011
IEEE
Non-rigid structure from motion (NRSFM) is a difficult, underconstrained problem in computer vision. The standard approach in NRSFM constrains 3D shape deformation using a linear...
CVPR
2004
IEEE
14 years 9 months ago
2004
IEEE
Background modeling is an important component of many vision systems. Existing work in the area has mostly addressed scenes that consist of static or quasi-static structures. When...
DAGM
2006
Springer
13 years 11 months ago
2006
Springer
Abstract. Isomap is a highly popular manifold learning and dimensionality reduction technique that effectively performs multidimensional scaling on estimates of geodesic distances....