206 search results - page 4 / 42 » PCA in Autocorrelation Space |
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...
NIPS
2003
13 years 9 months ago
2003
In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...
ICPR
2008
IEEE
14 years 2 months ago
2008
IEEE
This paper identifies a novel feature space to address the problem of human face recognition from still images. This is based on the PCA space of the features extracted by a new m...
JMM2
2006
13 years 7 months ago
2006
We propose a technique for gait recognition from motion capture data based on two successive stages of principal component analysis (PCA) on kinematic data. The first stage of PCA ...
SLSFS
2005
Springer
14 years 1 months ago
2005
Springer
We present a method which uses example pairs of equal or unequal class labels to select a subspace with near optimal metric properties in a kernel-induced Hilbert space. A represen...