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Multiresolution Hybrid Approaches for Automated Face Recognition
University of Edinburgh, Scotland, United Kingdom August 05-August 08
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AHS.2007.77Second NASA/ESA Conference on Adaptiv ...
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Paul Nicholl, Queen?s University, Belfast, UK
Abbes Amira, Brunel University, UK
Djamel Bouchaffra, Oakland University, Rochester, MI
Ronald H. Perrott, Queen?s University, Belfast, UK
This paper presents an evaluation of three classifiers using the discrete wavelet transform (DWT) as a feature extractor. The thrust is to investigate the impact of DWT with its various filter banks on the HMM, PCA and SHMM classifiers. In addition, we have developed a novel approach that combines the multiresolution feature of the discrete wavelet transform with the local interactions of the facial structures expressed through the structural hidden Markov model (SHMM). Tests have been carried out on the AT&T and Essex face databases, which show that DWT/SHMM outperforms both the DWT/HMM and DWT/PCA with an 8% increase in accuracy.
Citation:
Paul Nicholl, Abbes Amira, Djamel Bouchaffra, Ronald H. Perrott, "Multiresolution Hybrid Approaches for Automated Face Recognition," ahs, pp.89-96, Second NASA/ESA Conference on Adaptive Hardware and Systems (AHS 2007), 2007
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