Abstract
The paper investigates the impact that the face-image color space has on the verification performance of two popular face recognition procedures, i.e., the Fisherface approach and the Gabor-Fisher classifier - GFC. Experimental results on the XM2VTS database show that the Fisherface technique performs best when features are extracted from the Cr component of the YCbCr color space, while the performance of the Gabor-Fisher classifier is optimized when grey-scale intensity face-images are used for feature extraction. Based on these findings, a novel face recognition framework that combines the Fisherface and the GFC method is introduced in this paper and its feasibility demonstrated in a comparative study where, in addition to the proposed method, six widely used feature extraction techniques were tested for their face verification performance.
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BibTeX (Download)
@inproceedings{ERK2007,
title = {Color spaces for face recognition},
author = {Vitomir \v{S}truc, France Miheli\v{c}, Nikola Pave\v{s}i\'{c}},
url = {http://luks.fe.uni-lj.si/nluks/wp-content/uploads/2014/08/ERK2007.pdf},
year = {2007},
date = {2007-01-01},
booktitle = {Proceedings of the International Electrotechnical and Computer Science Conference (ERK'07)},
pages = {171-174},
address = {Portoro\v{z}, Slovenia},
abstract = {The paper investigates the impact that the face-image color space has on the verification performance of two popular face recognition procedures, i.e., the Fisherface approach and the Gabor-Fisher classifier - GFC. Experimental results on the XM2VTS database show that the Fisherface technique performs best when features are extracted from the Cr component of the YCbCr color space, while the performance of the Gabor-Fisher classifier is optimized when grey-scale intensity face-images are used for feature extraction. Based on these findings, a novel face recognition framework that combines the Fisherface and the GFC method is introduced in this paper and its feasibility demonstrated in a comparative study where, in addition to the proposed method, six widely used feature extraction techniques were tested for their face verification performance.},
key = {ERK2007},
keywords = {biometrics, color spaces, computer vision, erk, face recognition, local conference},
pubstate = {published},
tppubtype = {inproceedings}
}