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Authors: Chaudhary Muhammad Aqdus Ilyas ; Mohammad A. Haque ; Matthias Rehm ; Kamal Nasrollahi and Thomas B. Moeslund

Affiliation: Aalborg University (AAU), Denmark

ISBN: 978-989-758-290-5

ISSN: 2184-4321

Keyword(s): Computer Vision, Face Detection, Facial Landmarks, Facial Expressions, Convolution Neural Networks, Long-Short Term Memory, Traumatic Brain Injured Patients.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Computer Vision, Visualization and Computer Graphics ; Enterprise Information Systems ; Human and Computer Interaction ; Human-Computer Interaction

Abstract: In this paper, we investigate the issues associated with facial expression recognition of Traumatic Brain Insured (TBI) patients in a realistic scenario. These patients have restricted or limited muscle movements with reduced facial expressions along with non-cooperative behavior, impaired reasoning and inappropriate responses. All these factors make automatic understanding of their expressions more complex. While the existing facial expression recognition systems showed high accuracy by taking data from healthy subjects, their performance is yet to be proved for real TBI patient data by considering the aforementioned challenges. To deal with this, we devised scenarios for data collection from the real TBI patients, collected data which is very challenging to process, devised effective way of data preprocessing so that good quality faces can be extracted from the patients facial video for expression analysis, and finally, employed a state-of-the-art deep learning framework to exploit spatio-temporal information of facial video frames in expression analysis. The experimental results confirms the difficulty in processing real TBI patients data, while showing that better face quality ensures better performance in this case. (More)

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Paper citation in several formats:
Ilyas, C.; Haque, M.; Rehm, M.; Nasrollahi, K. and Moeslund, T. (2018). Facial Expression Recognition for Traumatic Brain Injured Patients.In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP, ISBN 978-989-758-290-5, ISSN 2184-4321, pages 522-530. DOI: 10.5220/0006721305220530

@conference{visapp18,
author={Chaudhary Muhammad Aqdus Ilyas. and Mohammad A. Haque. and Matthias Rehm. and Kamal Nasrollahi. and Thomas B. Moeslund.},
title={Facial Expression Recognition for Traumatic Brain Injured Patients},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP,},
year={2018},
pages={522-530},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006721305220530},
isbn={978-989-758-290-5},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP,
TI - Facial Expression Recognition for Traumatic Brain Injured Patients
SN - 978-989-758-290-5
AU - Ilyas, C.
AU - Haque, M.
AU - Rehm, M.
AU - Nasrollahi, K.
AU - Moeslund, T.
PY - 2018
SP - 522
EP - 530
DO - 10.5220/0006721305220530

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