Automatic pose correction for local feature-based face authentication

Daniel González-Jiménez; Federico Sukno; José Luis Alba-Castro; Alejandro F Frangi

doi:10.1007/11789239_37

Automatic pose correction for local feature-based face authentication

Daniel González-Jiménez^*, Federico Sukno, José Luis Alba-Castro, Alejandro F Frangi

^*Corresponding author for this work

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

Abstract

In this paper, we present an automatic face authentication system. Accurate segmentation of prominent facial features is accomplished by means of an extension of the Active Shape Model (ASM) approach, the so-called Active Shape Model with Invariant Optimal Features (IOF-ASM). Once the face has been segmented, a pose correction step is applied, so that frontal face images are synthesized. For the generation of these virtual images, we make use of a subset of the shape parameters extracted from a training dataset and Thin Plate Splines texture mapping. Afterwards, sets of local features are computed from these virtual images. The performance of the system is demonstrated on configurations I and II of the XM2VTS database.

Original language	English
Title of host publication	Articulated Motion and Deformable Objects - 4th International Conference, AMDO 2006, Proceedings
Publisher	Springer-Verlag Italia
Pages	356-365
Number of pages	10
ISBN (Print)	354036031X, 9783540360315
DOIs	https://doi.org/10.1007/11789239_37
Publication status	Published - 2006
Event	4th International Conference on Articulated Motion and Deformable Objects, AMDO 2006 - Port d'Andratx, Mallorca, Spain Duration: 11 Jul 2006 → 14 Jul 2006

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4069 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	4th International Conference on Articulated Motion and Deformable Objects, AMDO 2006
Country/Territory	Spain
City	Port d'Andratx, Mallorca
Period	11/07/06 → 14/07/06

Keywords

Automatic Segmentation
Face Authentication
Pose Correction

Access to Document

10.1007/11789239_37

Cite this

González-Jiménez, D., Sukno, F., Alba-Castro, J. L., & Frangi, A. F. (2006). Automatic pose correction for local feature-based face authentication. In Articulated Motion and Deformable Objects - 4th International Conference, AMDO 2006, Proceedings (pp. 356-365). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4069 LNCS). Springer-Verlag Italia. https://doi.org/10.1007/11789239_37

González-Jiménez, Daniel ; Sukno, Federico ; Alba-Castro, José Luis et al. / Automatic pose correction for local feature-based face authentication. Articulated Motion and Deformable Objects - 4th International Conference, AMDO 2006, Proceedings. Springer-Verlag Italia, 2006. pp. 356-365 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Automatic pose correction for local feature-based face authentication",

abstract = "In this paper, we present an automatic face authentication system. Accurate segmentation of prominent facial features is accomplished by means of an extension of the Active Shape Model (ASM) approach, the so-called Active Shape Model with Invariant Optimal Features (IOF-ASM). Once the face has been segmented, a pose correction step is applied, so that frontal face images are synthesized. For the generation of these virtual images, we make use of a subset of the shape parameters extracted from a training dataset and Thin Plate Splines texture mapping. Afterwards, sets of local features are computed from these virtual images. The performance of the system is demonstrated on configurations I and II of the XM2VTS database.",

keywords = "Automatic Segmentation, Face Authentication, Pose Correction",

author = "Daniel Gonz{\'a}lez-Jim{\'e}nez and Federico Sukno and Alba-Castro, {Jos{\'e} Luis} and Frangi, {Alejandro F}",

year = "2006",

doi = "10.1007/11789239_37",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

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booktitle = "Articulated Motion and Deformable Objects - 4th International Conference, AMDO 2006, Proceedings",

address = "Italy",

note = "4th International Conference on Articulated Motion and Deformable Objects, AMDO 2006 ; Conference date: 11-07-2006 Through 14-07-2006",

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González-Jiménez, D, Sukno, F, Alba-Castro, JL & Frangi, AF 2006, Automatic pose correction for local feature-based face authentication. in Articulated Motion and Deformable Objects - 4th International Conference, AMDO 2006, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4069 LNCS, Springer-Verlag Italia, pp. 356-365, 4th International Conference on Articulated Motion and Deformable Objects, AMDO 2006, Port d'Andratx, Mallorca, Spain, 11/07/06. https://doi.org/10.1007/11789239_37

Automatic pose correction for local feature-based face authentication. / González-Jiménez, Daniel; Sukno, Federico; Alba-Castro, José Luis et al.
Articulated Motion and Deformable Objects - 4th International Conference, AMDO 2006, Proceedings. Springer-Verlag Italia, 2006. p. 356-365 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4069 LNCS).

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

TY - GEN

T1 - Automatic pose correction for local feature-based face authentication

AU - González-Jiménez, Daniel

AU - Sukno, Federico

AU - Alba-Castro, José Luis

AU - Frangi, Alejandro F

PY - 2006

Y1 - 2006

N2 - In this paper, we present an automatic face authentication system. Accurate segmentation of prominent facial features is accomplished by means of an extension of the Active Shape Model (ASM) approach, the so-called Active Shape Model with Invariant Optimal Features (IOF-ASM). Once the face has been segmented, a pose correction step is applied, so that frontal face images are synthesized. For the generation of these virtual images, we make use of a subset of the shape parameters extracted from a training dataset and Thin Plate Splines texture mapping. Afterwards, sets of local features are computed from these virtual images. The performance of the system is demonstrated on configurations I and II of the XM2VTS database.

AB - In this paper, we present an automatic face authentication system. Accurate segmentation of prominent facial features is accomplished by means of an extension of the Active Shape Model (ASM) approach, the so-called Active Shape Model with Invariant Optimal Features (IOF-ASM). Once the face has been segmented, a pose correction step is applied, so that frontal face images are synthesized. For the generation of these virtual images, we make use of a subset of the shape parameters extracted from a training dataset and Thin Plate Splines texture mapping. Afterwards, sets of local features are computed from these virtual images. The performance of the system is demonstrated on configurations I and II of the XM2VTS database.

KW - Automatic Segmentation

KW - Face Authentication

KW - Pose Correction

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M3 - Conference contribution

AN - SCOPUS:33746608540

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SN - 9783540360315

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

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González-Jiménez D, Sukno F, Alba-Castro JL, Frangi AF. Automatic pose correction for local feature-based face authentication. In Articulated Motion and Deformable Objects - 4th International Conference, AMDO 2006, Proceedings. Springer-Verlag Italia. 2006. p. 356-365. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11789239_37

Automatic pose correction for local feature-based face authentication

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