Multiresolution hybrid approaches for automated face recognition

被引：0

作者：

Nicholl, Paul ^{[1
]}

Bouchaffra, Djamel ^{[2
]}

Amira, Abbes ^{[3
]}

Perrott, Ronald H. ^{[1
]}

机构：

[1] Queens Univ Belfast, Sch Elect Elect Engn & Comp Sci, Belfast BT12 6BJ, Antrim, North Ireland

[2] Oakland Univ, Sch Engn & Comp Sci, Rochester, MI 48309 USA

[3] Brunel Univ, Sch Engn & Design, Uxbridge UB8 3PH, Middx, England

来源：

NASA/ESA CONFERENCE ON ADAPTIVE HARDWARE AND SYSTEMS, PROCEEDINGS | 2007年

关键词：

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：89 / +

页数：3

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