326 search results - page 8 / 66 » Principal Component Analysis for Distributed Data Sets with ... |
ICCV
2001
IEEE
14 years 10 months ago
2001
IEEE
Principal Component Analysis (PCA) has been widely used for the representation of shape, appearance, and motion. One drawback of typical PCA methods is that they are least squares...
CORR
2007
Springer
13 years 8 months ago
2007
Springer
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a linear combination of the input variables while constraining the number of nonze...
ICML
2007
IEEE
14 years 9 months ago
2007
IEEE
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a particular linear combination of the input variables while constraining the numb...
IJCNN
2006
IEEE
14 years 2 months ago
2006
IEEE
— We introduce in this paper methods for finding mutually corresponding dependent components from two different but related data sets in an unsupervised (blind) manner. The basi...
ICCV
2011
IEEE
12 years 8 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...