Recognition of emotions by the emotional feedback through behavioral human poses
2015 (English)In: International Journal of Computer Science Issues, ISSN 1694-0784, E-ISSN 1694-0814, Vol. 12, no 1, 7-17 p.Article in journal (Refereed) Published
The sensory perceptions from humans are intertwined channels,which assemble diverse data in order to decrypt emotionalinformation. Just by associations, humans can mix emotionalinformation, i.e. emotion detection through facial expressionscriteria, emotional speech, and the challenging field of emotionalbody language over the body poses and motion. In this work, wepresent an approach that can predict six basic universal emotionscollected by responses linked to human body poses, from acomputational perspective. The emotional outputs could be fedas inputs to a synthetic socially skilled agent capable ofinteraction, in the context of socially intelligent systems. Themethodology uses a classification technique of information fromsix images extracted from a video, entirely developed using themotion sensing input device of Xbox 360 by Microsoft. We aretaking into account that the emotional body language containsadvantageous information about the emotional state of humans,especially when bodily reaction brings about consciousemotional experiences. The body parts are windows that showemotions and they would be particularly suitable to decodingaffective states. The group of extracted images is merged in oneimage with all the relevant information. The recovered image willserve as input to the classifiers. The analysis of images fromhuman body poses makes it possible to obtain relevantinformation through the combination of proper data in the sameimage. It is shown by experimental results that the SVM candetect emotion with good accuracy compared to other classifiers.
Place, publisher, year, edition, pages
2015. Vol. 12, no 1, 7-17 p.
Detection of Emotional Information, Affective Computing, Body Gesture Analysis, Robotics, Classification, Machine Learning.
Research subject Computer and Systems Sciences
IdentifiersURN: urn:nbn:se:su:diva-122138OAI: oai:DiVA.org:su-122138DiVA: diva2:865110