標題: Face recognition using nonparametric-weighted Fisherfaces
作者: Li, Dong-Lin
Prasad, Mukesh
Hsu, Sheng-Chih
Hong, Chao-Ting
Lin, Chin-Teng
資訊工程學系
電機工程學系
Department of Computer Science
Department of Electrical and Computer Engineering
關鍵字: appearance-based vision;face recognition;nonparametric-weighted feature extraction (NWFE)
公開日期: 2012
摘要: This study presents an appearance-based face recognition scheme called the nonparametric-weighted Fisherfaces (NW-Fisherfaces). Pixels in a facial image are considered as coordinates in a high-dimensional space and are transformed into a face subspace for analysis by using nonparametric-weighted feature extraction (NWFE). According to previous studies of hyperspectral image classification, NWFE is a powerful tool for extracting hyperspectral image features. The Fisherfaces method maximizes the ratio of between-class scatter to that of within-class scatter. In this study, the proposed NW-Fisherfaces weighted the between-class scatter to emphasize the boundary structure of the transformed face subspace and, therefore, enhances the separability for different persons' face. The proposed NW-Fisherfaces was compared with Orthogonal Laplacianfaces, Eigenfaces, Fisherfaces, direct linear discriminant analysis, and null space linear discriminant analysis methods for tests on five facial databases. Experimental results showed that the proposed approach outperforms other feature extraction methods for most databases.
URI: http://hdl.handle.net/11536/16381
http://dx.doi.org/92
ISSN: 1687-6180
DOI: 92
期刊: EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING
顯示於類別:期刊論文


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