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Authors: Taoufik Ben Abdallah 1 ; Radhouane Guermazi 2 and Mohamed Hammami 1

Affiliations: 1 Sfax University, Tunisia ; 2 Saudi Electronic University, Saudi Arabia

Keyword(s): Facial Expression Recognition, Local Binary Pattern, Eigenfaces, Controlled Environment, Uncontrolled Environment.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Data Mining ; Databases and Information Systems Integration ; Emotional and Affective Computing ; Enterprise Information Systems ; Human-Computer Interaction ; Multimedia Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: This paper suggests an approach to automatic facial expression recognition for images of frontal faces. Two methods of appearance features extraction is combined: Local Binary Pattern (LBP) on the whole face region and Eigenfaces on the eyes-eyebrows and/or on the mouth regions. Support Vector Machines (SVM), K Nearest Neighbors (KNN) and MultiLayer Perceptron (MLP) are applied separately as learning technique to generate classifiers for facial expression recognition. Furthermore, we conduct to the many empirical studies to fix the optimal parameters of the approach. We use three baseline databases to validate our approach in which we record interesting results compared to the related works regardless of using faces under controlled and uncontrolled environment.

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Paper citation in several formats:
Ben Abdallah, T., Guermazi, R. and Hammami, M. (2017). Facial Expression Recognition Improvement through an Appearance Features Combination. In Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 3: ICEIS; ISBN 978-989-758-249-3; ISSN 2184-4992, SciTePress, pages 111-118. DOI: 10.5220/0006288301110118

@conference{iceis17,
author={Taoufik {Ben Abdallah} and Radhouane Guermazi and Mohamed Hammami},
title={Facial Expression Recognition Improvement through an Appearance Features Combination},
booktitle={Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 3: ICEIS},
year={2017},
pages={111-118},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006288301110118},
isbn={978-989-758-249-3},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 19th International Conference on Enterprise Information Systems - Volume 3: ICEIS
TI - Facial Expression Recognition Improvement through an Appearance Features Combination
SN - 978-989-758-249-3
IS - 2184-4992
AU - Ben Abdallah, T.
AU - Guermazi, R.
AU - Hammami, M.
PY - 2017
SP - 111
EP - 118
DO - 10.5220/0006288301110118
PB - SciTePress

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