Semantics in Visual Information Retrieval
IEEE MultiMedia
Semantic Annotation of Sports Videos
IEEE MultiMedia
Correlation between stimulated emotion extracted from EEG and its manifestation on facial expression
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
EEG-based personalized digital experience
UAHCI'11 Proceedings of the 6th international conference on Universal access in human-computer interaction: users diversity - Volume Part II
3D fuzzy GIST to analyze emotional features in movies
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
| Hi-index | 0.01 |
This paper proposes a novel emotion understanding system based on brain activity and ''GIST'' to categorize emotions reflected by natural scenes. According to the intensified relationship of human emotion and the brain activity, functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) are used to analyze and classify emotional states stimulated by a natural scene. The ''GIST'' is used to extract the visual low-level features, which are used as input signals to a classifier for obtaining the high-level emotional gist of a natural scene. Mean opinion scores are used for teaching signals of the classifier. Considering the way a human brain is responding to the same visual stimuli, a machine will be able to extract the emotional features of natural scenes using the ''GIST'' and the EEG signals, judge the emotions reflected by the nature scenes and achieve interaction with a human in terms of emotional sharing through the EEG signals. The experimental results demonstrate that positive and negative emotions can be distinguished.