Three-dimensional face recognition in the presence of facial expressions: An annotated deformable model approach

Ioannis A. Kakadiaris; Georgios Passalis; George Toderici; Mohammed N. Murtuza; Yunliang Lu; Nikos Karampatziakis; Theoharis Theoharis

doi:10.1109/TPAMI.2007.1017

Three-dimensional face recognition in the presence of facial expressions: An annotated deformable model approach

Ioannis A. Kakadiaris, Georgios Passalis, George Toderici, Mohammed N. Murtuza, Yunliang Lu, Nikos Karampatziakis, Theoharis Theoharis

Research output: Contribution to journal › Article › peer-review

417 Scopus citations

Abstract

In this paper, we present the computational tools and a hardware prototype for 3D face recognition. Full automation is provided through the use of advanced multistage alignment algorithms, resilience to facial expressions by employing a deformable model framework, and invariance to 3D capture devices through suitable preprocessing steps. In addition, scalability in both time and space is achieved by converting 3D facial scans into compact metadata. We present our results on the largest known, and now publicly available, Face Recognition Grand Challenge 3D facial database consisting of several thousand scans. To the best of our knowledge, this is the highest performance reported on the FRGC v2 database for the 3D modality.

Original language	English (US)
Pages (from-to)	640-649
Number of pages	10
Journal	IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume	29
Issue number	4
DOIs	https://doi.org/10.1109/TPAMI.2007.1017
State	Published - Apr 2007

Keywords

Face and gesture recognition
Information search and retrieval

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Computational Theory and Mathematics
Artificial Intelligence
Applied Mathematics

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10.1109/TPAMI.2007.1017

Cite this

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title = "Three-dimensional face recognition in the presence of facial expressions: An annotated deformable model approach",

abstract = "In this paper, we present the computational tools and a hardware prototype for 3D face recognition. Full automation is provided through the use of advanced multistage alignment algorithms, resilience to facial expressions by employing a deformable model framework, and invariance to 3D capture devices through suitable preprocessing steps. In addition, scalability in both time and space is achieved by converting 3D facial scans into compact metadata. We present our results on the largest known, and now publicly available, Face Recognition Grand Challenge 3D facial database consisting of several thousand scans. To the best of our knowledge, this is the highest performance reported on the FRGC v2 database for the 3D modality.",

keywords = "Face and gesture recognition, Information search and retrieval",

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note = "Funding Information: The authors are grateful for the support provided by the Department of Computer Science, University of Houston, the Texas Learning and Computation Center, University of Houston, the Central Intelligence Agency, and the Southwest Public Safety Technology Center, University of Houston.",

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doi = "10.1109/TPAMI.2007.1017",

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AU - Kakadiaris, Ioannis A.

AU - Passalis, Georgios

AU - Toderici, George

AU - Murtuza, Mohammed N.

AU - Lu, Yunliang

AU - Karampatziakis, Nikos

AU - Theoharis, Theoharis

N1 - Funding Information: The authors are grateful for the support provided by the Department of Computer Science, University of Houston, the Texas Learning and Computation Center, University of Houston, the Central Intelligence Agency, and the Southwest Public Safety Technology Center, University of Houston.

PY - 2007/4

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N2 - In this paper, we present the computational tools and a hardware prototype for 3D face recognition. Full automation is provided through the use of advanced multistage alignment algorithms, resilience to facial expressions by employing a deformable model framework, and invariance to 3D capture devices through suitable preprocessing steps. In addition, scalability in both time and space is achieved by converting 3D facial scans into compact metadata. We present our results on the largest known, and now publicly available, Face Recognition Grand Challenge 3D facial database consisting of several thousand scans. To the best of our knowledge, this is the highest performance reported on the FRGC v2 database for the 3D modality.

AB - In this paper, we present the computational tools and a hardware prototype for 3D face recognition. Full automation is provided through the use of advanced multistage alignment algorithms, resilience to facial expressions by employing a deformable model framework, and invariance to 3D capture devices through suitable preprocessing steps. In addition, scalability in both time and space is achieved by converting 3D facial scans into compact metadata. We present our results on the largest known, and now publicly available, Face Recognition Grand Challenge 3D facial database consisting of several thousand scans. To the best of our knowledge, this is the highest performance reported on the FRGC v2 database for the 3D modality.

KW - Face and gesture recognition

KW - Information search and retrieval

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Three-dimensional face recognition in the presence of facial expressions: An annotated deformable model approach

Abstract

Keywords

ASJC Scopus subject areas

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