DocumentCode
2961357
Title
Emotion recognition in natural scene images based on brain activity and gist
Author
Zhang, Qing ; Lee, Minho
Author_Institution
Sch. of Electr. Eng. & Comput. Sci., Kyungpook Nat. Univ., Daegu
fYear
2008
fDate
1-8 June 2008
Firstpage
3050
Lastpage
3057
Abstract
Artificial emotion study will be of utmost importance in future artificial intelligence research. In this paper, an emotion understanding system based on brain activity and ldquoGISTrdquo is newly proposed to categorize emotions reflected by natural scenes. According to the strong 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 ldquoGISTrdquo is used to represent the emotional gist of the natural scene. In other words, by taking the way human brain responding to the same stimulus into consideration, a machine will be able to visually extract the emotional features of natural scenes and achieve interaction with a human in terms of emotional sharing. The experimental results show that positive and negative emotions can be distinguished, and a monkey robot head that can share emotion with human subject during watching an image is implemented.
Keywords
biomedical MRI; electroencephalography; emotion recognition; feature extraction; image classification; image colour analysis; image representation; image sensors; medical image processing; natural scenes; principal component analysis; support vector machines; EEG sensor; PCA preprocessor; SVM classifier; artificial intelligence; brain activity; electroencephalography; emotion recognition; emotion understanding system; emotional GIST representation; emotional feature extraction; emotional sharing; emotional state classification; fMRI; functional magnetic resonance imaging; image color information; natural scene image; visual stimuli; Artificial intelligence; Brain; Electroencephalography; Emotion recognition; Feature extraction; Humans; Image analysis; Layout; Magnetic analysis; Magnetic resonance imaging;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location
Hong Kong
ISSN
1098-7576
Print_ISBN
978-1-4244-1820-6
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2008.4634229
Filename
4634229
Link To Document