Generalised nearest feature line for subspace learning

Y. Pang*, Y. Yuan, X. Li

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
Pages (from-to)1079-1080
Number of pages2
JournalElectronics letters
Volume43
Issue number20
DOIs
Publication statusPublished - 8 Oct 2007

Fingerprint

Face recognition
Extrapolation
Pattern recognition
Interpolation
Experiments

Keywords

  • discriminators
  • extrapolation
  • interpolation
  • software prototyping

Cite this

Pang, Y. ; Yuan, Y. ; Li, X. / Generalised nearest feature line for subspace learning. In: Electronics letters. 2007 ; Vol. 43, No. 20. pp. 1079-1080.
@article{fc24db547e6447d6b3e8faf497aed8d9,
title = "Generalised nearest feature line for subspace learning",
abstract = "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.",
keywords = "discriminators, extrapolation, interpolation, software prototyping",
author = "Y. Pang and Y. Yuan and X. Li",
year = "2007",
month = "10",
day = "8",
doi = "10.1049/el:20072176",
language = "English",
volume = "43",
pages = "1079--1080",
journal = "Electronics letters",
issn = "0013-5194",
publisher = "IET",
number = "20",

}

Generalised nearest feature line for subspace learning. / Pang, Y.; Yuan, Y.; Li, X.

In: Electronics letters, Vol. 43, No. 20, 08.10.2007, p. 1079-1080.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Generalised nearest feature line for subspace learning

AU - Pang, Y.

AU - Yuan, Y.

AU - Li, X.

PY - 2007/10/8

Y1 - 2007/10/8

N2 - 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.

AB - 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.

KW - discriminators

KW - extrapolation

KW - interpolation

KW - software prototyping

UR - http://www.scopus.com/inward/record.url?scp=34748847406&partnerID=8YFLogxK

U2 - 10.1049/el:20072176

DO - 10.1049/el:20072176

M3 - Article

AN - SCOPUS:34748847406

VL - 43

SP - 1079

EP - 1080

JO - Electronics letters

JF - Electronics letters

SN - 0013-5194

IS - 20

ER -