Title :
Emotion modeling using Fuzzy Cognitive Maps
Author :
Akinci, Hasan Murat ; Yesil, Engin
Author_Institution :
Control & Autom. Eng. Dept., Istanbul Tech. Univ., Istanbul, Turkey
Abstract :
In this study, Fuzzy Cognitive Map (FCM) modeling technique on emotion recognition problem with regression of arousal and valence values is applied and Big Bang - Big Crunch learning method is used for developing the model. Emotions play a critical role of humans´ behaviors, beliefs, motivations and decisions. Developing a model between bodily responses and emotional states of a human is an extremely challenging problem in affective computing area. In this study, DEAP dataset, which is publicly available, is used as a dataset. The set contains the recordings of physiological modalities for participant, each participant viewing video clips and reporting emotional states with using self assessment manikins. The results of various simulations show that FCM is a useful and convenient tool for emotion modeling.
Keywords :
behavioural sciences computing; cognitive systems; emotion recognition; fuzzy set theory; learning (artificial intelligence); psychology; Big Bang-Big Crunch learning method; DEAP dataset; FCM modeling technique; affective computing; arousal value regression; emotion modeling; emotion recognition problem; fuzzy cognitive maps; human behaviors; human beliefs; human bodily response; human decisions; human emotional state; human motivations; physiological modality; self assessment manikins; valence value regression; video clip viewing; Computational modeling; Correlation; Emotion recognition; Feature extraction; Fuzzy cognitive maps; Physiology; Skin;
Conference_Titel :
Computational Intelligence and Informatics (CINTI), 2013 IEEE 14th International Symposium on
Conference_Location :
Budapest
Print_ISBN :
978-1-4799-0194-4
DOI :
10.1109/CINTI.2013.6705252
