This paper presents characterization of affect (valence and arousal) using the Magnetoencephalogram (MEG) brain signal. We attempt single-trial classification of movie and music videos with MEG responses extracted from seven participants. The main findings of this study are that: (i) the MEG signal effectively encodes affective viewer responses, (ii) clip arousal is better predicted than valence employing MEG and (iii) prediction performance is better for movie clips as compared to music videos.



Titolo: Decoding Affect in Videos Employing the MEG Brain Signal
Autori: 
Kia, Seyed Mostafa
Avesani, Paolo
mostra contributor esterni 
Data di pubblicazione: 2013
Abstract: This paper presents characterization of affect (valence and arousal) using the Magnetoencephalogram (MEG) brain signal. We attempt single-trial classification of movie and music videos with MEG responses extracted from seven participants. The main findings of this study are that: (i) the MEG signal effectively encodes affective viewer responses, (ii) clip arousal is better predicted than valence employing MEG and (iii) prediction performance is better for movie clips as compared to music videos.
Handle: http://hdl.handle.net/11582/199011
Appare nelle tipologie:4.1 Contributo in Atti di convegno

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http://hdl.handle.net/11582/199011
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