基于gaborface的2DPCA和集成多通道模型(2D)2PCA分类的人脸识别

2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications Pub Date : 2007-04-01 DOI:10.1109/CISDA.2007.368128

Lin Wang, Yongping Li, Chengbo Wang, Hongzhou Zhang

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引用次数: 15

摘要

本文介绍了基于Gaborface的2DPCA和基于二维Gaborface矩阵而不是变换ID特征向量的(2D)2PCA分类方法。提出了两种使用Gaborface库的策略:集成Gaborface表示(EGFR)和多通道Gaborface表示(MGFR)。在ORL和Yale数据库上的实验结果证明了该方法的可行性。其中，基于mgfr的(2D)2 PCA方法对ORL数据库的识别准确率达到100%，对每类5个训练样本的Yale数据库的识别准确率达到98.89%

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Face Recognition using Gaborface-based 2DPCA and (2D)2PCA Classification with Ensemble and Multichannel Model

This paper introduces Gaborface-based 2DPCA and (2D)2PCA classification method based on 2D Gaborface matrices rather than transformed ID feature vectors. Two kinds of strategies to use the bank of Gaborfaces are proposed: ensemble Gaborface representation (EGFR) and multichannel Gaborface representation (MGFR). The feasibility of our method is proved with the experimental results on the ORL and Yale databases. In particular, the MGFR-based (2D)2 PCA method achieves 100% recognition accuracy for ORL database, and 98.89% accuracy for Yale database with five training samples per class

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2007 IEEE Symposium on Computational Intelligence in Security and Defense Applications

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