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DOI: 10.14569/IJARAI.2016.050608
PDF

A Model for Facial Emotion Inference Based on Planar Dynamic Emotional Surfaces

Author 1: J. P. P. Ruivo
Author 2: T. Negreiros
Author 3: M. R. P. Barretto
Author 4: B. Tinen

International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 5 Issue 6, 2016.

  • Abstract and Keywords
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Abstract: Emotions have direct influence on the human life and are of great importance in relationships and in the way interactions between individuals develop. Because of this, they are also important for the development of human-machine interfaces that aim to maintain a natural and friendly interaction with its users. In the development of social robots, which this work aims for, a suitable interpretation of the emotional state of the person interacting with the social robot is indispensable. The focus of this paper is the development of a mathematical model for recognizing emotional facial expressions in a sequence of frames. Firstly, a face tracker algorithm is used to find and keep track of faces in images; then the found faces are fed into the model developed in this work, which consists of an instantaneous emotional expression classifier, a Kalman filter and a dynamic classifier that gives the final output of the model.

Keywords: emotion recognition, facial emotion, Kalman filter, machine learning

J. P. P. Ruivo, T. Negreiros, M. R. P. Barretto and B. Tinen, “A Model for Facial Emotion Inference Based on Planar Dynamic Emotional Surfaces” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 5(6), 2016. http://dx.doi.org/10.14569/IJARAI.2016.050608

@article{Ruivo2016,
title = {A Model for Facial Emotion Inference Based on Planar Dynamic Emotional Surfaces},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2016.050608},
url = {http://dx.doi.org/10.14569/IJARAI.2016.050608},
year = {2016},
publisher = {The Science and Information Organization},
volume = {5},
number = {6},
author = {J. P. P. Ruivo and T. Negreiros and M. R. P. Barretto and B. Tinen}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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