loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Author: Zakia Hammal

Affiliation: Laboratory of Images and Signals, France

Keyword(s): facial expression classification, dynamic modelling, transferable belief model, facial feature behavior.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Biomedical Signal Processing ; Data Manipulation ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Soft Computing

Abstract: In the present contribution a novel approach for dynamic facial expressions classification is presented and discussed. The presented approach is based on the use of the Transferable Belief Model applied to static facial expression classification studied in previous developments. The system is able to recognize pure facial expressions, i.e., Joy, Surprise, Disgust and Neutral as well as their mixtures. Additionally, this approach is able to deal with all facial feature configurations that does not correspond to any of the cited expression, i.e., Unknown expressions. The major improvement of this former work consists in the introduction of the temporal evolution of the facial feature behavior. Initially, the temporal information is introduced to improve the robustness of the frame-by-frame classification by the correction of errors due to the automatic segmentation process. In addition since a facial expression is the result of a dynamic and progressive combination of facial features b ehavior, which is not always synchronous, a frame-by-frame classification is not sufficient. To overcome this constraint, we propose the introduction of the temporal information inside the TBM fusion framework. The recognition is accomplished by combining all facial feature behaviors between the beginning and the end of an expression sequence independently to their chronological order. Then the final decision is taken on the whole sequence and consequently, the recognition becomes more robust and accurate. Experimental results on the Hammal Caplier database demonstrate the improvement on the frame-by-frame classification and the ability to recognize entire facial expression sequences. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 34.201.28.181

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Hammal, Z. (2006). DYNAMIC FACIAL EXPRESSION UNDERSTANDING BASED ON TEMPORAL MODELLING OF TRANSFERABLE BELIEF MODEL. In Proceedings of the First International Conference on Computer Vision Theory and Applications (VISIGRAPP 2006) - Volume 2: VISAPP; ISBN 972-8865-40-6; ISSN 2184-4321, SciTePress, pages 93-100. DOI: 10.5220/0001377600930100

@conference{visapp06,
author={Zakia Hammal.},
title={DYNAMIC FACIAL EXPRESSION UNDERSTANDING BASED ON TEMPORAL MODELLING OF TRANSFERABLE BELIEF MODEL},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications (VISIGRAPP 2006) - Volume 2: VISAPP},
year={2006},
pages={93-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001377600930100},
isbn={972-8865-40-6},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the First International Conference on Computer Vision Theory and Applications (VISIGRAPP 2006) - Volume 2: VISAPP
TI - DYNAMIC FACIAL EXPRESSION UNDERSTANDING BASED ON TEMPORAL MODELLING OF TRANSFERABLE BELIEF MODEL
SN - 972-8865-40-6
IS - 2184-4321
AU - Hammal, Z.
PY - 2006
SP - 93
EP - 100
DO - 10.5220/0001377600930100
PB - SciTePress