Feature extraction and face verification using gabor and gaussian mixture models

Jesus Olivares-Mercado; Gabriel Sanchez-Perez; Mariko Nakano-Miyatake; Hector Perez-Meana

doi:10.1007/978-3-540-76631-5_73

Feature extraction and face verification using gabor and gaussian mixture models

Jesus Olivares-Mercado, Gabriel Sanchez-Perez, Mariko Nakano-Miyatake, Hector Perez-Meana

Escuela Superior de Ingeniería Mecánica y Eléctrica (ESIME), Unidad Culhuacán

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

This paper proposes a faces verification in which the feature extraction is carried out using the discrete Gabor function (DGF), while the Gaussian Mixture Model (GMM) is used in the face verification stage. Evaluation results using standard data bases with different parameters, such as the number of mixtures and the number of face used for training show that proposed system provides better results that other proposed systems with a correct verification rate larger than 95%. Although, as happens in must face recognition systems, the verification rate decreases when the target faces present some rotation degrees.

Original language	English
Title of host publication	MICAI 2007
Subtitle of host publication	Advances in Artificial Intelligence - 6th Mexican International Conference on Artificial Intelligence, Proceedings
Publisher	Springer Verlag
Pages	769-778
Number of pages	10
ISBN (Print)	9783540766308
DOIs	https://doi.org/10.1007/978-3-540-76631-5_73
State	Published - 2007
Event	6th Mexican International Conference on Artificial Intelligence, MICAI 2007 - Aguascalientes, Mexico Duration: 4 Nov 2007 → 10 Nov 2007

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4827 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	6th Mexican International Conference on Artificial Intelligence, MICAI 2007
Country/Territory	Mexico
City	Aguascalientes
Period	4/11/07 → 10/11/07

Keywords

Face verification
Gabor functions
Gaussian mixture model

Access to Document

10.1007/978-3-540-76631-5_73

Cite this

Olivares-Mercado, J., Sanchez-Perez, G., Nakano-Miyatake, M., & Perez-Meana, H. (2007). Feature extraction and face verification using gabor and gaussian mixture models. In MICAI 2007: Advances in Artificial Intelligence - 6th Mexican International Conference on Artificial Intelligence, Proceedings (pp. 769-778). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4827 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-540-76631-5_73

Olivares-Mercado, Jesus ; Sanchez-Perez, Gabriel ; Nakano-Miyatake, Mariko et al. / Feature extraction and face verification using gabor and gaussian mixture models. MICAI 2007: Advances in Artificial Intelligence - 6th Mexican International Conference on Artificial Intelligence, Proceedings. Springer Verlag, 2007. pp. 769-778 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{36fe4c509d724c5798b5a31204a8eeda,

title = "Feature extraction and face verification using gabor and gaussian mixture models",

abstract = "This paper proposes a faces verification in which the feature extraction is carried out using the discrete Gabor function (DGF), while the Gaussian Mixture Model (GMM) is used in the face verification stage. Evaluation results using standard data bases with different parameters, such as the number of mixtures and the number of face used for training show that proposed system provides better results that other proposed systems with a correct verification rate larger than 95%. Although, as happens in must face recognition systems, the verification rate decreases when the target faces present some rotation degrees.",

keywords = "Face verification, Gabor functions, Gaussian mixture model",

author = "Jesus Olivares-Mercado and Gabriel Sanchez-Perez and Mariko Nakano-Miyatake and Hector Perez-Meana",

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publisher = "Springer Verlag",

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note = "6th Mexican International Conference on Artificial Intelligence, MICAI 2007 ; Conference date: 04-11-2007 Through 10-11-2007",

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Olivares-Mercado, J , Sanchez-Perez, G , Nakano-Miyatake, M & Perez-Meana, H 2007, Feature extraction and face verification using gabor and gaussian mixture models. in MICAI 2007: Advances in Artificial Intelligence - 6th Mexican International Conference on Artificial Intelligence, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4827 LNAI, Springer Verlag, pp. 769-778, 6th Mexican International Conference on Artificial Intelligence, MICAI 2007, Aguascalientes, Mexico, 4/11/07. https://doi.org/10.1007/978-3-540-76631-5_73

Feature extraction and face verification using gabor and gaussian mixture models. / Olivares-Mercado, Jesus ; Sanchez-Perez, Gabriel ; Nakano-Miyatake, Mariko et al.
MICAI 2007: Advances in Artificial Intelligence - 6th Mexican International Conference on Artificial Intelligence, Proceedings. Springer Verlag, 2007. p. 769-778 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4827 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Feature extraction and face verification using gabor and gaussian mixture models

AU - Olivares-Mercado, Jesus

AU - Sanchez-Perez, Gabriel

AU - Nakano-Miyatake, Mariko

AU - Perez-Meana, Hector

PY - 2007

Y1 - 2007

N2 - This paper proposes a faces verification in which the feature extraction is carried out using the discrete Gabor function (DGF), while the Gaussian Mixture Model (GMM) is used in the face verification stage. Evaluation results using standard data bases with different parameters, such as the number of mixtures and the number of face used for training show that proposed system provides better results that other proposed systems with a correct verification rate larger than 95%. Although, as happens in must face recognition systems, the verification rate decreases when the target faces present some rotation degrees.

AB - This paper proposes a faces verification in which the feature extraction is carried out using the discrete Gabor function (DGF), while the Gaussian Mixture Model (GMM) is used in the face verification stage. Evaluation results using standard data bases with different parameters, such as the number of mixtures and the number of face used for training show that proposed system provides better results that other proposed systems with a correct verification rate larger than 95%. Although, as happens in must face recognition systems, the verification rate decreases when the target faces present some rotation degrees.

KW - Face verification

KW - Gabor functions

KW - Gaussian mixture model

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U2 - 10.1007/978-3-540-76631-5_73

DO - 10.1007/978-3-540-76631-5_73

M3 - Contribución a la conferencia

SN - 9783540766308

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 769

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BT - MICAI 2007

PB - Springer Verlag

T2 - 6th Mexican International Conference on Artificial Intelligence, MICAI 2007

Y2 - 4 November 2007 through 10 November 2007

ER -

Olivares-Mercado J , Sanchez-Perez G , Nakano-Miyatake M , Perez-Meana H. Feature extraction and face verification using gabor and gaussian mixture models. In MICAI 2007: Advances in Artificial Intelligence - 6th Mexican International Conference on Artificial Intelligence, Proceedings. Springer Verlag. 2007. p. 769-778. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-540-76631-5_73

Feature extraction and face verification using gabor and gaussian mixture models

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