Generalised nearest feature line for subspace learning

Y. Pang; Y. Yuan; X. Li

doi:10.1049/el:20072176

Generalised nearest feature line for subspace learning

Y. Pang, Y. Yuan, X. Li

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39 引用（Scopus）

摘要

Nearest feature line (NFL) is a powerful tool in pattern recognition, which generalises the representational capacity of available prototypes by using linear interpolation and extrapolation between the feature points. NFL is generalised to subspace learning so that the obtained subspace has desirable discriminating ability. Experiments on face recognition demonstrate its effectiveness.

源语言	英语
页（从-至）	1079-1080
页数	2
期刊	Electronics Letters
卷	43
期	20
DOI	https://doi.org/10.1049/el:20072176
出版状态	已出版 - 2007
已对外发布	是

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Generalised nearest feature line for subspace learning

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