Journal
NEUROCOMPUTING
Volume 73, Issue 16-18, Pages 3264-3272Publisher
ELSEVIER
DOI: 10.1016/j.neucom.2010.04.001
Keywords
Emotion understanding; EEG; Facial expression; GIST; IAPS; Neuro-fuzzy inference model
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Funding
- Korea government (NEST) [2009-0070465]
- Ministry of Education, Science and Technology [2009-0082262]
- National Research Foundation of Korea [2009-0070465, 2009-0082262] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
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This paper proposes a novel emotion understanding system based on human brain activity, facial expression, and GIST to categorize emotions reflected by natural scenes, and to share emotions between humans and the developed system. Three modalities are adopted in the proposed system, including an electroencephalography (EEG) signal, human facial expressions stimulated by a natural scene, and GIST', which is used to extract low-level features and represent the primitive emotional gist of the scene. Through integrated analyzing the EEG of humans with different facial expressions and visual information from natural scene images, the proposed system can create clustering for different emotional features and construct some primitive knowledge about emotions. Using an interactive process through time, the proposed system can infer a human's emotional status based on a neuro-fuzzy inference model and obtain a mental ability to understand emotions more accurately. The mean opinion score (MOS) is used to evaluate the performance of the proposed emotion understanding system. Experimental results demonstrate that an understanding of positive and negative emotions can be achieved under human supervision. (C) 2010 Elsevier B.V. All rights reserved.
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