Identifying universal facial emotion markers for automatic 3D facial expression recognition

Amal Azazi; Syaheerah Lebai Lutfi; Ibrahim Venkat

doi:10.1109/ICCOINS.2014.6868369

Identifying universal facial emotion markers for automatic 3D facial expression recognition

Amal Azazi, Syaheerah Lebai Lutfi, Ibrahim Venkat

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

4 Citations (Scopus)

Abstract

Facial expressions convey human emotions as a simple and effective non-verbal communication method. Motivated by this special characteristic, facial expression recognition rapidly gains attention in social computing fields, especially in Human Computer Interaction (HCI). Identifying the optimal set of facial emotion markers is an important technique that not only reduces the feature vector dimensionality, but also impacts the recognition accuracy. In this paper, we propose a new emotion marker identification algorithm for automatic and person-independent 3D facial expression recognition system. First, we mapped the 3D face images into the 2D plane via conformal geometry to reduce the dimensionality. Then, the identification algorithm is designed to seek the best discriminative markers and the classifier parameters simultaneously by integrating three techniques viz., Differential Evolution (DE), Support Vector Machine (SVM) and Speed Up Robust Feature (SURF). The proposed system yielded an average recognition rate of 79% and outperformed the previous studies using the Bosphorus database.

Original language	English
Title of host publication	2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014
Subtitle of host publication	Proceedings
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Number of pages	6
ISBN (Electronic)	9781479943913
DOIs	https://doi.org/10.1109/ICCOINS.2014.6868369
Publication status	Published - 1 Jan 2014
Externally published	Yes
Event	2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - Kuala Lumpur, Malaysia Duration: 3 Jun 2014 → 5 Jun 2014

Conference

Conference	2014 International Conference on Computer and Information Sciences, ICCOINS 2014
Country/Territory	Malaysia
City	Kuala Lumpur
Period	3/06/14 → 5/06/14

Keywords

3D facial expression recognition
DE
Emotion marker identification
HCI
SURF
SVM

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10.1109/ICCOINS.2014.6868369

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Azazi, A., Lutfi, S. L., & Venkat, I. (2014). Identifying universal facial emotion markers for automatic 3D facial expression recognition. In 2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 : Proceedings [6868369] Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ICCOINS.2014.6868369

Azazi, Amal ; Lutfi, Syaheerah Lebai ; Venkat, Ibrahim. / Identifying universal facial emotion markers for automatic 3D facial expression recognition. 2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 : Proceedings. Institute of Electrical and Electronics Engineers (IEEE), 2014.

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title = "Identifying universal facial emotion markers for automatic 3D facial expression recognition",

abstract = "Facial expressions convey human emotions as a simple and effective non-verbal communication method. Motivated by this special characteristic, facial expression recognition rapidly gains attention in social computing fields, especially in Human Computer Interaction (HCI). Identifying the optimal set of facial emotion markers is an important technique that not only reduces the feature vector dimensionality, but also impacts the recognition accuracy. In this paper, we propose a new emotion marker identification algorithm for automatic and person-independent 3D facial expression recognition system. First, we mapped the 3D face images into the 2D plane via conformal geometry to reduce the dimensionality. Then, the identification algorithm is designed to seek the best discriminative markers and the classifier parameters simultaneously by integrating three techniques viz., Differential Evolution (DE), Support Vector Machine (SVM) and Speed Up Robust Feature (SURF). The proposed system yielded an average recognition rate of 79% and outperformed the previous studies using the Bosphorus database.",

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Azazi, A, Lutfi, SL & Venkat, I 2014, Identifying universal facial emotion markers for automatic 3D facial expression recognition. in 2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 : Proceedings., 6868369, Institute of Electrical and Electronics Engineers (IEEE), 2014 International Conference on Computer and Information Sciences, ICCOINS 2014, Kuala Lumpur, Malaysia, 3/06/14. https://doi.org/10.1109/ICCOINS.2014.6868369

Identifying universal facial emotion markers for automatic 3D facial expression recognition. / Azazi, Amal; Lutfi, Syaheerah Lebai; Venkat, Ibrahim.
2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 : Proceedings. Institute of Electrical and Electronics Engineers (IEEE), 2014. 6868369.

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

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Azazi A, Lutfi SL, Venkat I. Identifying universal facial emotion markers for automatic 3D facial expression recognition. In 2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014 : Proceedings. Institute of Electrical and Electronics Engineers (IEEE). 2014. 6868369 doi: 10.1109/ICCOINS.2014.6868369

Identifying universal facial emotion markers for automatic 3D facial expression recognition

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Keywords

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