Compressed Submanifold Multifactor Analysis

Although widely used, Multilinear PCA (MPCA), one of the leading multilinear analysis methods, still suffers from four major drawbacks. First, it is very sensitive to outliers and noise. Second, it is unable to cope with missing values. Third, it is computationally expensive since MPCA deals with la...

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Veröffentlicht in:	IEEE transactions on pattern analysis and machine intelligence 2017-03, Vol.39 (3), p.444-456
Hauptverfasser:	Khoa Luu, Savvides, Marios, Bui, Tien D., Suen, Ching Y.
Format:	Artikel
Sprache:	eng
Schlagworte:	Approximation algorithms compressed sensing Face Face recognition Lighting Manifolds (mathematics) Multiaccess communication multifactor analysis Noise sensitivity Outliers (statistics) Principal component analysis random projection Tensile stress Tensor analysis ℓ<sub xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"/>-norm optimization
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