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Using Hidden Markov Models and Wavelets for Face Recognition
Mantova, Italy September 17-September 19
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICIAP.2003.123402412th International Conference on Imag ...
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M. Bicego, U. Castellani, V. Murino, "Using Hidden Markov Models and Wavelets for Face Recognition," Image Analysis and Processing, International Conference on, pp. 52, 12th International Conference on Image Analysis and Processing (ICIAP'03), 2003.
 
 
BibTex
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@article{ 10.1109/ICIAP.2003.1234024,
author = {M. Bicego and U. Castellani and V. Murino},
title = {Using Hidden Markov Models and Wavelets for Face Recognition},
journal ={Image Analysis and Processing, International Conference on},
volume = {0},
year = {2003},
isbn = {0-7695-1948-2},
pages = {52},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICIAP.2003.1234024},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Image Analysis and Processing, International Conference on
TI - Using Hidden Markov Models and Wavelets for Face Recognition
SN - 0-7695-1948-2
SP
EP
A1 - M. Bicego,
A1 - U. Castellani,
A1 - V. Murino,
PY - 2003
KW - null
VL - 0
JA - Image Analysis and Processing, International Conference on
ER -
 
M. Bicego, Università di Verona
U. Castellani, Università di Verona
V. Murino, Università di Verona
In this paper, a new system for face recognition is proposed, based on Hidden Markov Models (HMMs) and wavelet coding. A sequence of overlapping sub-images is extracted from each face image, computing the wavelet coefficients for each of them. The whole sequence is then modelled by using Hidden Markov Models. The proposed method is compared with a DCT coefficients-based approach [9], showing comparable results. By using an accurate model selection procedure, we show that results proposed in [9] can be improved even more. The obtained results outperform all results presented in the literature on the Olivetti Research Laboratory (ORL) face database, reaching a 100% recognition rate. These performances proves the suitability of HMMs to deal with the new JPEG2000 image compression standard.
Citation:
M. Bicego, U. Castellani, V. Murino, "Using Hidden Markov Models and Wavelets for Face Recognition," iciap, pp.52, 12th International Conference on Image Analysis and Processing (ICIAP'03), 2003
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