Euler principal component analysis

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Euler principal component analysis

Principal Component Analysis (PCA) is perhaps the most prominent learning tool for dimensionality reduction in pattern recognition and computer vision. However, the ℓ 2-norm employed by standard PCA is not robust to outliers. In this paper, we propose a kernel PCA method for fast and robust PCA, whi...

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Bibliographic Details
Main Authors:	Liwicki, Stephan, Tzimiropoulos, Georgios, Zafeiriou, Stefanos, Pantic, Maja
Format:	Article
Published:	Springer 2013
Subjects:	Euler PCA Robust Subspace Online Learning Tracking Background Modeling
Online Access:	https://eprints.nottingham.ac.uk/31427/

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