Face recognition based on discriminant waveletfaces

Limin Cui; Yuan Yan Tang; Fucheng Liao; Xiufeng Du

doi:10.1109/ICSMC.2007.4413902

Face recognition based on discriminant waveletfaces

Limin Cui
, Yuan Yan Tang
, Fucheng Liao
, Xiufeng Du

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

2 Citations (Scopus)

Abstract

Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) have been widely applied in the face detection and recognition, yet still they have some limitations such as poor discriminative power and large computational load. This paper presents a method for face recognition using discriminant waveletfaces. Firstly wavelet transform is used to decompose the face image into different frequency subbands for extracting feature - waveletfaces, and then the discriminant analysis of PCA plus LDA is performed on the chosen subband. Finally the nearest neighbor classifier is adopted to make decision. In comparison with the traditional discriminant analysis, the experiments show that the proposed approach has better recognition rate and can reduce the computational load.

Original language	English
Title of host publication	2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007
Publisher	IEEE
Pages	3561-3565
Number of pages	5
ISBN (Electronic)	9781424409914
ISBN (Print)	1424409918, 9781424409907
DOIs	https://doi.org/10.1109/ICSMC.2007.4413902
Publication status	Published - 7 Oct 2007
Event	2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007 - Montreal, QC, Canada Duration: 7 Oct 2007 → 10 Oct 2007

Publication series

Name	Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
Publisher	IEEE
ISSN (Print)	1062-922X

Conference

Conference	2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007
Country/Territory	Canada
City	Montreal, QC
Period	7/10/07 → 10/10/07

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Access to Document

10.1109/ICSMC.2007.4413902

Cite this

@inproceedings{5757ee265376425e89136baa02b6548d,

title = "Face recognition based on discriminant waveletfaces",

abstract = "Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) have been widely applied in the face detection and recognition, yet still they have some limitations such as poor discriminative power and large computational load. This paper presents a method for face recognition using discriminant waveletfaces. Firstly wavelet transform is used to decompose the face image into different frequency subbands for extracting feature - waveletfaces, and then the discriminant analysis of PCA plus LDA is performed on the chosen subband. Finally the nearest neighbor classifier is adopted to make decision. In comparison with the traditional discriminant analysis, the experiments show that the proposed approach has better recognition rate and can reduce the computational load.",

author = "Limin Cui and Tang, \{Yuan Yan\} and Fucheng Liao and Xiufeng Du",

note = "Publisher copyright: {\textcopyright} 2007 IEEE; 2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007 ; Conference date: 07-10-2007 Through 10-10-2007",

year = "2007",

month = oct,

day = "7",

doi = "10.1109/ICSMC.2007.4413902",

language = "English",

isbn = "1424409918",

series = "Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics",

publisher = "IEEE",

pages = "3561--3565",

booktitle = "2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007",

address = "United States",

}

Cui, L, Tang, YY, Liao, F & Du, X 2007, Face recognition based on discriminant waveletfaces. in 2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics, IEEE, pp. 3561-3565, 2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007, Montreal, QC, Canada, 7/10/07. https://doi.org/10.1109/ICSMC.2007.4413902

Face recognition based on discriminant waveletfaces. / Cui, Limin; Tang, Yuan Yan; Liao, Fucheng et al.
2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007. IEEE, 2007. p. 3561-3565 (Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Face recognition based on discriminant waveletfaces

AU - Cui, Limin

AU - Tang, Yuan Yan

AU - Liao, Fucheng

AU - Du, Xiufeng

PY - 2007/10/7

Y1 - 2007/10/7

N2 - Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) have been widely applied in the face detection and recognition, yet still they have some limitations such as poor discriminative power and large computational load. This paper presents a method for face recognition using discriminant waveletfaces. Firstly wavelet transform is used to decompose the face image into different frequency subbands for extracting feature - waveletfaces, and then the discriminant analysis of PCA plus LDA is performed on the chosen subband. Finally the nearest neighbor classifier is adopted to make decision. In comparison with the traditional discriminant analysis, the experiments show that the proposed approach has better recognition rate and can reduce the computational load.

AB - Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) have been widely applied in the face detection and recognition, yet still they have some limitations such as poor discriminative power and large computational load. This paper presents a method for face recognition using discriminant waveletfaces. Firstly wavelet transform is used to decompose the face image into different frequency subbands for extracting feature - waveletfaces, and then the discriminant analysis of PCA plus LDA is performed on the chosen subband. Finally the nearest neighbor classifier is adopted to make decision. In comparison with the traditional discriminant analysis, the experiments show that the proposed approach has better recognition rate and can reduce the computational load.

UR - https://www.scopus.com/pages/publications/40949111364

U2 - 10.1109/ICSMC.2007.4413902

DO - 10.1109/ICSMC.2007.4413902

M3 - Conference proceeding

AN - SCOPUS:40949111364

SN - 1424409918

SN - 9781424409907

T3 - Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics

SP - 3561

EP - 3565

BT - 2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007

PB - IEEE

T2 - 2007 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2007

Y2 - 7 October 2007 through 10 October 2007

ER -

Face recognition based on discriminant waveletfaces

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Conference

UN SDGs

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