502 search results - page 19 / 101 » Principal Component Analysis for Sparse High-Dimensional Dat... |
105
Voted
ICRA
1998
IEEE
15 years 4 months ago
1998
IEEE
1 sensors is to construct a structural description from sensor data and to match this description to a previously acquired model [Crowley 85]. An alternative is to project individu...
AMCS
2008
15 years 17 days ago
2008
Principal component analysis (PCA) is a powerful fault detection and isolation method. However, the classical PCA which is based on the estimation of the sample mean and covariance...
119
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CVPR
2008
IEEE
16 years 2 months ago
2008
IEEE
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...
113
Voted
ISBI
2006
IEEE
2006
IEEE
Mixture principal component analysis for distribution volume parametric imaging in brain PET studies
16 years 1 months ago
In this paper, we present a mixture Principal Component Analysis (mPCA)-based approach for voxel level quantification of dynamic positron emission tomography (PET) data in brain s...
96
Voted
PR
2006
2006
Correspondence matching using kernel principal components analysis and label consistency constraints
15 years 11 days ago
This paper investigates spectral approaches to the problem of point pattern matching. We make two contributions. First, we consider rigid point-set alignment. Here we show how ker...