Towards a full emotional system
Year: 2012
Type: article
Abstract: This study proposes a system that is able to classify a facial expression in one of the six categories, namely, Joy, Disgust, Anger, Sadness, Fear and Surprise and also to assign to each expression its intensity in the range: High, Medium and Low. This is carried out in two independent and parallel processes. Permanent and transient facial features are detected from still images, and pertinent information about the presence of transient features on specific facial regions and about facial distances computed from permanent facial features is extracted. Both classification and quantification processes are based on transient and permanent features. The belief theory is used with the two processes because of its ability in fusing data coming from different sensors. The system outputs a recognised and quantified expression. The quantification process allows recognising a new subset of expressions deduced from the basic ones. Indeed, by associating to each expression three intensities low, medium and high, we deduce three facial expressions. Finally, a set of 18 facial expressions is categorised instead of the six ones. Experimental results are given to show the system classification accuracy.
Authors: Khadoudja Ghanem, Alice Caplier
Institutions: University Frères Mentouri Constantine 1, GIPSA-Lab
Language: English
Topic: Emotion and Mood Recognition
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1991983507