Imperial College London

STEFANOS ZAFEIRIOU, PhD

Faculty of EngineeringDepartment of Computing

Professor in Machine Learning & Computer Vision
 
 
 
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Contact

 

+44 (0)20 7594 8461s.zafeiriou Website CV

 
 
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Location

 

375Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Tzimiropoulos:2011:10.1109/FG.2011.5771457,
author = {Tzimiropoulos, G and Zafeiriou, S and Pantic, M},
doi = {10.1109/FG.2011.5771457},
pages = {553--558},
title = {Principal component analysis of image gradient orientations for face recognition},
url = {http://dx.doi.org/10.1109/FG.2011.5771457},
year = {2011}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - We introduce the notion of Principal Component Analysis (PCA) of image gradient orientations. As image data is typically noisy, but noise is substantially different from Gaussian, traditional PCA of pixel intensities very often fails to estimate reliably the low-dimensional subspace of a given data population. We show that replacing intensities with gradient orientations and the 2 norm with a cosine-based distance measure offers, to some extend, a remedy to this problem. Our scheme requires the eigen-decomposition of a covariance matrix and is as computationally efficient as standard 2 intensity-based PCA. We demonstrate some of its favorable properties for the application of face recognition. © 2011 IEEE.
AU - Tzimiropoulos,G
AU - Zafeiriou,S
AU - Pantic,M
DO - 10.1109/FG.2011.5771457
EP - 558
PY - 2011///
SP - 553
TI - Principal component analysis of image gradient orientations for face recognition
UR - http://dx.doi.org/10.1109/FG.2011.5771457
ER -