Face recognition using wireframe model across facial expressions

Zahid Riaz; Christoph Mayer; Michael Beetz; Bernd Radig

doi:10.1007/978-3-642-04391-8_16

Face recognition using wireframe model across facial expressions

Zahid Riaz, Christoph Mayer, Michael Beetz, Bernd Radig

TUM Emeriti of Excellence

Technical University of Munich

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

Abstract

This paper describes face recognition across facial expressions variations. We focus on an automatic feature extraction technique which is not only efficient but also accurate for person identification. A 3D wireframe model is fitted to face images using a robust objective function. Furthermore, we extract structural and textural information which is coupled with temoral information from the motion of local facial features. The extracted information is combined to form a feature vector descriptor for each image. This set of features has been tested on two databases for face recognition across facial expressions. We use Bayesian Network (BN) and Binary Decision Trees (BDT) as classifiers. The developed system is automatic, real-time capable and efficient.

Original language	English
Title of host publication	Biometric ID Management and Multimodal Communication - Joint COST 2101 and 2102 International Conference, BioID_MultiComm 2009, Proceedings
Pages	122-129
Number of pages	8
DOIs	https://doi.org/10.1007/978-3-642-04391-8_16
State	Published - 2009
Event	Joint COST 2101 and 2102 International Conference on Biometric ID Management and Multimodal Communication, BioID_MultiComm 2009 - Madrid, Spain Duration: 16 Sep 2009 → 18 Sep 2009

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	5707 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	Joint COST 2101 and 2102 International Conference on Biometric ID Management and Multimodal Communication, BioID_MultiComm 2009
Country/Territory	Spain
City	Madrid
Period	16/09/09 → 18/09/09

Keywords

Face recognition
Feature extraction
Image classification
Model based image analysis

Access to Document

10.1007/978-3-642-04391-8_16

Cite this

Riaz, Z., Mayer, C., Beetz, M., & Radig, B. (2009). Face recognition using wireframe model across facial expressions. In Biometric ID Management and Multimodal Communication - Joint COST 2101 and 2102 International Conference, BioID_MultiComm 2009, Proceedings (pp. 122-129). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5707 LNCS). https://doi.org/10.1007/978-3-642-04391-8_16

Riaz, Zahid ; Mayer, Christoph ; Beetz, Michael et al. / Face recognition using wireframe model across facial expressions. Biometric ID Management and Multimodal Communication - Joint COST 2101 and 2102 International Conference, BioID_MultiComm 2009, Proceedings. 2009. pp. 122-129 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Face recognition using wireframe model across facial expressions",

abstract = "This paper describes face recognition across facial expressions variations. We focus on an automatic feature extraction technique which is not only efficient but also accurate for person identification. A 3D wireframe model is fitted to face images using a robust objective function. Furthermore, we extract structural and textural information which is coupled with temoral information from the motion of local facial features. The extracted information is combined to form a feature vector descriptor for each image. This set of features has been tested on two databases for face recognition across facial expressions. We use Bayesian Network (BN) and Binary Decision Trees (BDT) as classifiers. The developed system is automatic, real-time capable and efficient.",

keywords = "Face recognition, Feature extraction, Image classification, Model based image analysis",

author = "Zahid Riaz and Christoph Mayer and Michael Beetz and Bernd Radig",

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Riaz, Z, Mayer, C, Beetz, M & Radig, B 2009, Face recognition using wireframe model across facial expressions. in Biometric ID Management and Multimodal Communication - Joint COST 2101 and 2102 International Conference, BioID_MultiComm 2009, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 5707 LNCS, pp. 122-129, Joint COST 2101 and 2102 International Conference on Biometric ID Management and Multimodal Communication, BioID_MultiComm 2009, Madrid, Spain, 16/09/09. https://doi.org/10.1007/978-3-642-04391-8_16

Face recognition using wireframe model across facial expressions. / Riaz, Zahid; Mayer, Christoph; Beetz, Michael et al.
Biometric ID Management and Multimodal Communication - Joint COST 2101 and 2102 International Conference, BioID_MultiComm 2009, Proceedings. 2009. p. 122-129 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5707 LNCS).

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

TY - GEN

T1 - Face recognition using wireframe model across facial expressions

AU - Riaz, Zahid

AU - Mayer, Christoph

AU - Beetz, Michael

AU - Radig, Bernd

PY - 2009

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N2 - This paper describes face recognition across facial expressions variations. We focus on an automatic feature extraction technique which is not only efficient but also accurate for person identification. A 3D wireframe model is fitted to face images using a robust objective function. Furthermore, we extract structural and textural information which is coupled with temoral information from the motion of local facial features. The extracted information is combined to form a feature vector descriptor for each image. This set of features has been tested on two databases for face recognition across facial expressions. We use Bayesian Network (BN) and Binary Decision Trees (BDT) as classifiers. The developed system is automatic, real-time capable and efficient.

AB - This paper describes face recognition across facial expressions variations. We focus on an automatic feature extraction technique which is not only efficient but also accurate for person identification. A 3D wireframe model is fitted to face images using a robust objective function. Furthermore, we extract structural and textural information which is coupled with temoral information from the motion of local facial features. The extracted information is combined to form a feature vector descriptor for each image. This set of features has been tested on two databases for face recognition across facial expressions. We use Bayesian Network (BN) and Binary Decision Trees (BDT) as classifiers. The developed system is automatic, real-time capable and efficient.

KW - Face recognition

KW - Feature extraction

KW - Image classification

KW - Model based image analysis

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SN - 9783642043901

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

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BT - Biometric ID Management and Multimodal Communication - Joint COST 2101 and 2102 International Conference, BioID_MultiComm 2009, Proceedings

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Riaz Z, Mayer C, Beetz M, Radig B. Face recognition using wireframe model across facial expressions. In Biometric ID Management and Multimodal Communication - Joint COST 2101 and 2102 International Conference, BioID_MultiComm 2009, Proceedings. 2009. p. 122-129. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-642-04391-8_16

Face recognition using wireframe model across facial expressions

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Keywords

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