Various Decomposition Methods Applied to Face Recognition

Jaepil Ko; Eunju Kim; Hyeran Byun

Various Decomposition Methods Applied to Face Recognition

Jaepil Ko, Eunju Kim, Hyeran Byun

College of Computing

Research output: Contribution to conference › Paper › peer-review

Abstract

Face recognition has mainly focused on face representation, so a simple classifier is frequently used. For a robust system, it is common to construct a multiclass classifier by combining outputs of several binary ones. In this paper, we overviews basic decomposition and decoding schemes and propose new methods then give empirical results of recognition performance on the ORL face dataset.

Original language	English
Pages	2175-2180
Number of pages	6
Publication status	Published - 2003
Event	International Joint Conference on Neural Networks 2003 - Portland, OR, United States Duration: 2003 Jul 20 → 2003 Jul 24

Other

Other	International Joint Conference on Neural Networks 2003
Country/Territory	United States
City	Portland, OR
Period	03/7/20 → 03/7/24

All Science Journal Classification (ASJC) codes

Software
Artificial Intelligence

Cite this

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title = "Various Decomposition Methods Applied to Face Recognition",

abstract = "Face recognition has mainly focused on face representation, so a simple classifier is frequently used. For a robust system, it is common to construct a multiclass classifier by combining outputs of several binary ones. In this paper, we overviews basic decomposition and decoding schemes and propose new methods then give empirical results of recognition performance on the ORL face dataset.",

author = "Jaepil Ko and Eunju Kim and Hyeran Byun",

year = "2003",

language = "English",

pages = "2175--2180",

note = "International Joint Conference on Neural Networks 2003 ; Conference date: 20-07-2003 Through 24-07-2003",

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TY - CONF

T1 - Various Decomposition Methods Applied to Face Recognition

AU - Ko, Jaepil

AU - Kim, Eunju

AU - Byun, Hyeran

PY - 2003

Y1 - 2003

N2 - Face recognition has mainly focused on face representation, so a simple classifier is frequently used. For a robust system, it is common to construct a multiclass classifier by combining outputs of several binary ones. In this paper, we overviews basic decomposition and decoding schemes and propose new methods then give empirical results of recognition performance on the ORL face dataset.

AB - Face recognition has mainly focused on face representation, so a simple classifier is frequently used. For a robust system, it is common to construct a multiclass classifier by combining outputs of several binary ones. In this paper, we overviews basic decomposition and decoding schemes and propose new methods then give empirical results of recognition performance on the ORL face dataset.

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UR - http://www.scopus.com/inward/citedby.url?scp=0141633967&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0141633967

SP - 2175

EP - 2180

T2 - International Joint Conference on Neural Networks 2003

Y2 - 20 July 2003 through 24 July 2003

ER -

Various Decomposition Methods Applied to Face Recognition

Abstract

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All Science Journal Classification (ASJC) codes

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