Authors:
Saki Morita
and
Kuniaki Uehara
Affiliation:
Kobe University, Japan
Keyword(s):
Facial expression analysis, finite element method, angular metrics for shape similarity, emotion classification.
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:
Recent development in multimedia urges the need for an engineering study of the human face in communication media and man-machine interface. In this paper, we introduce a method not only for recognizing facial expression and human emotion, but for extracting rules from them as well. Facial data can be obtained by considering the relative position of each feature point in time series. Our approach estimates the behavior of muscles of facial expression from these data, and evaluates it to recognize facial expressions. In the recognition process, essential parameters that cause visible change of the face are extracted by estimating the force vectors of points on the face. The force vectors are calculated from displacements of points on the face by using FEM (Finite Element Method). To compare the multi-streams of force vectors of each facial expression effectively, A new similarity metric AMSS (Angular Metrics for Shape Similarity) is proposed. Finally, experiments of recognition of fac
ial expressions shows that usable results are achieved even with few testees in our approach and variable rule corresponding AUs can be detected.
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