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
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;
Conference_Titel :
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-1820-6
Electronic_ISBN :
1098-7576
DOI :
10.1109/IJCNN.2008.4634229