98 search results - page 9 / 20 » On Point Sampling Versus Space Sampling for Dimensionality R... |
ICCV
2007
IEEE
14 years 1 months ago
2007
IEEE
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
CVPR
2007
IEEE
14 years 9 months ago
2007
IEEE
The estimation of head pose angle from face images is an integral component of face recognition systems, human computer interfaces and other human-centered computing applications....
JMLR
2006
13 years 7 months ago
2006
Dimensionality reduction is an important pre-processing step in many applications. Linear discriminant analysis (LDA) is a classical statistical approach for supervised dimensiona...
NIPS
1997
13 years 9 months ago
1997
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
ACII
2005
Springer
13 years 9 months ago
2005
Springer
The null space N(St) of total scatter matrix St contains no useful information for pattern classification. So, discarding the null space N(St) results in dimensionality reduction ...