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» Motion Processing using Variable Harmonic Components
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ECCV
2002
Springer
14 years 10 months ago
Robust Parameterized Component Analysis
Principal ComponentAnalysis (PCA) has been successfully applied to construct linear models of shape, graylevel, and motion. In particular, PCA has been widely used to model the var...
Fernando De la Torre, Michael J. Black
ICA
2007
Springer
14 years 2 months ago
Subspaces of Spatially Varying Independent Components in fMRI
Abstract. In contrast to the traditional hypothesis-driven methods, independent component analysis (ICA) is commonly used in functional magnetic resonance imaging (fMRI) studies to...
Jarkko Ylipaavalniemi, Ricardo Vigário
SPLC
2007
13 years 9 months ago
A Variability Modeling Method for Adaptable Services in Service-Oriented Computing
Publish-Discover-Compose paradigm of Service-Oriented Computing (SOC) presents a challenge on service applicability. Services are not just for predefined clients, rather for poten...
Soo Ho Chang, Soo Dong Kim
ICIP
2004
IEEE
14 years 10 months ago
Robust motion-based image segmentation using fusion
To support real-time tracking of objects in video sequences, there has been considerable effort directed at developing optical flow and general motion-based image segmentation alg...
Michael E. Farmer, Xiaoguang Lu, Hong Chen, Anil K...
ICCV
2001
IEEE
14 years 10 months ago
Robust Principal Component Analysis for Computer Vision
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...
Fernando De la Torre, Michael J. Black