Face Recognition Based on Gabor Features

Dat Tran; Xu Huang; Girija Chetty

doi:10.1109/EuVIP.2011.6045542

Face Recognition Based on Gabor Features

Dat Tran, Xu Huang, Girija Chetty

Information Systems

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

4 Citations (Scopus)

3 Downloads (Pure)

Abstract

The paper presents a novel approach for solving face recognition problem. We combine Gabor filters and Principal Component Analysis (PCA) to extract feature vectors; then we apply Support Vector Machine (SVM), the most powerful discriminative method, and AdaBoost, a meta-algorithm, for classification. Experiments for the proposed method have been conducted on two public face database AT&T and FERET. The results show that the proposed method could improve the classification rates

Original language	English
Title of host publication	Visual Information Processing EUVIP 2011, 3rd European Workshop
Editors	Azeddine Beghdadi, Abdesselam Bouzerdoum, Giuseppe Boccignone, Mohamed-Chaker Larabi
Place of Publication	Paris
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	264-269
Number of pages	6
Volume	1
ISBN (Print)	9781457700729
DOIs	https://doi.org/10.1109/EuVIP.2011.6045542
Publication status	Published - 2011
Event	European Workshop on Visual Information Processing - Paris, Paris, France Duration: 4 Jul 2011 → 6 Jul 2011

Conference

Conference	European Workshop on Visual Information Processing
Country/Territory	France
City	Paris
Period	4/07/11 → 6/07/11

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10.1109/EuVIP.2011.6045542

Cite this

@inproceedings{61825a52d30548ce90368cf7c2455802,

title = "Face Recognition Based on Gabor Features",

abstract = "The paper presents a novel approach for solving face recognition problem. We combine Gabor filters and Principal Component Analysis (PCA) to extract feature vectors; then we apply Support Vector Machine (SVM), the most powerful discriminative method, and AdaBoost, a meta-algorithm, for classification. Experiments for the proposed method have been conducted on two public face database AT&T and FERET. The results show that the proposed method could improve the classification rates",

keywords = "Face Recognition, Gabor Feature",

author = "Dat Tran and Xu Huang and Girija Chetty",

year = "2011",

doi = "10.1109/EuVIP.2011.6045542",

language = "English",

isbn = "9781457700729",

volume = "1",

pages = "264--269",

editor = "Azeddine Beghdadi and Abdesselam Bouzerdoum and Giuseppe Boccignone and Mohamed-Chaker Larabi",

booktitle = "Visual Information Processing EUVIP 2011, 3rd European Workshop",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States",

note = "European Workshop on Visual Information Processing ; Conference date: 04-07-2011 Through 06-07-2011",

}

Tran, D, Huang, X & Chetty, G 2011, Face Recognition Based on Gabor Features. in A Beghdadi, A Bouzerdoum, G Boccignone & M-C Larabi (eds), Visual Information Processing EUVIP 2011, 3rd European Workshop. vol. 1, IEEE, Institute of Electrical and Electronics Engineers, Paris, pp. 264-269, European Workshop on Visual Information Processing, Paris, France, 4/07/11. https://doi.org/10.1109/EuVIP.2011.6045542

Face Recognition Based on Gabor Features. / Tran, Dat; Huang, Xu ; Chetty, Girija.
Visual Information Processing EUVIP 2011, 3rd European Workshop. ed. / Azeddine Beghdadi; Abdesselam Bouzerdoum; Giuseppe Boccignone; Mohamed-Chaker Larabi. Vol. 1 Paris: IEEE, Institute of Electrical and Electronics Engineers, 2011. p. 264-269.

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

TY - GEN

T1 - Face Recognition Based on Gabor Features

AU - Tran, Dat

AU - Huang, Xu

AU - Chetty, Girija

PY - 2011

Y1 - 2011

N2 - The paper presents a novel approach for solving face recognition problem. We combine Gabor filters and Principal Component Analysis (PCA) to extract feature vectors; then we apply Support Vector Machine (SVM), the most powerful discriminative method, and AdaBoost, a meta-algorithm, for classification. Experiments for the proposed method have been conducted on two public face database AT&T and FERET. The results show that the proposed method could improve the classification rates

AB - The paper presents a novel approach for solving face recognition problem. We combine Gabor filters and Principal Component Analysis (PCA) to extract feature vectors; then we apply Support Vector Machine (SVM), the most powerful discriminative method, and AdaBoost, a meta-algorithm, for classification. Experiments for the proposed method have been conducted on two public face database AT&T and FERET. The results show that the proposed method could improve the classification rates

KW - Face Recognition

KW - Gabor Feature

U2 - 10.1109/EuVIP.2011.6045542

DO - 10.1109/EuVIP.2011.6045542

M3 - Conference contribution

SN - 9781457700729

VL - 1

SP - 264

EP - 269

BT - Visual Information Processing EUVIP 2011, 3rd European Workshop

A2 - Beghdadi, Azeddine

A2 - Bouzerdoum, Abdesselam

A2 - Boccignone, Giuseppe

A2 - Larabi, Mohamed-Chaker

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Paris

T2 - European Workshop on Visual Information Processing

Y2 - 4 July 2011 through 6 July 2011

ER -

Face Recognition Based on Gabor Features

Abstract

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