Title :
Decoding affect in videos employing the MEG brain signal
Author :
Abadi, Mojtaba Khomami ; Kia, Mohsen ; Subramanian, Ramanathan ; Avesani, Paolo ; Sebe, Nicu
Author_Institution :
Univ. of Trento, Trento, Italy
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.
Keywords :
magnetoencephalography; medical signal processing; signal classification; video signal processing; MEG brain signal; affect characterization; affective viewer response; arousal; clip arousal; magnetoencephalogram; movie; music video; prediction performance; single-trial classification; valence; Discrete cosine transforms; Feature extraction; Magnetic recording; Magnetic resonance imaging; Motion pictures; Time-frequency analysis; Videos;
Conference_Titel :
Automatic Face and Gesture Recognition (FG), 2013 10th IEEE International Conference and Workshops on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-5545-2
Electronic_ISBN :
978-1-4673-5544-5
DOI :
10.1109/FG.2013.6553809
