Browse > Article
http://dx.doi.org/10.9717/kmms.2018.21.1.001

An Analysis of EEG Signal Generated from Watching Aesthetic and Non-aesthetic Content  

Kim, Yong-Woo (Dept. of Digital Media, Catholic University of Korea)
Kang, Dong-Gyun (Dept. of Media Technology and Contents, Catholic University of Korea)
Kang, Hang-Bong (Dept. of Digital Media, Catholic University of Korea)
Publication Information
Abstract
Much research has been conducted to judge aesthetic value for a single type of stimuli, but research to determine aesthetic value when two kinds of stimuli are presented at the same time is not explored in depth. In this paper, we measure the difference between the presentation of visual stimuli like general image and the presentation of signboard image including text stimuli using EEG. In the experiment, two oddball tasks were performed for general images and signboard images, and EEG changes according to the aesthetic value of the images were measured. As a result, the change of ERP in signboard image was larger than that of general image. We confirmed that more visual information was received and processed when two stimuli were presented at the same time.
Keywords
EEG; ERP; Oddball paradigm; Aesthetic;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 H. Leder, B. Belke, A. Oeberst, and D. Augustin, "A Model of Aesthetic Appreciation and Aesthetic Judgments," British Journal of Psychology, Vol. 95, No.4, pp. 489-508, 2004.   DOI
2 A. Whitfield and J. Wiltshire, “Design Training and Aesthetic Evaluation: An Intergroup Comparison,” Journal of Environmental Psychology, Vol. 2, No. 2, pp. 109-117, 1982.   DOI
3 X. Lu, Z. Lin, H. Jin, J. Yang, and J.Z. Wang, "RAPID: Rating Pictorial Aesthetics using Deep Learning," Proceedings of the 22nd ACM International Conference on Multimedia, pp. 457-466, 2014.
4 X. Lu, Z. Lin, X. Shen, R. Mech, and J.Z. Wang, "Deep Multi-Patch Aggregation Network for Image Style, Aesthetics, and Quality Estimation," Proceedings of the IEEE International Conference on Computer Vision, pp. 990-998, 2015.
5 X. Tian, Z. Dong, K. Yang, and T. Mei, “Query-Dependent Aesthetic Model With Deep Learning for Photo Quality Assessment,” IEEE Transactions on Multimedia, Vol. 17, No. 11, pp. 2035-2048, 2015.   DOI
6 S. Kong, X. Shen, Z. Lin, R. Mech, and C. Fowlkes, "Photo Aesthetics Ranking Network with Attributes and Content Adaptation," Proceedings of the European Conference on Computer Vision, pp. 662-679, 2016.
7 L. Mai, H. Jin, and F. Liu, "Composition-Preserving Deep Photo Aesthetics Assessment," Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 497-506, 2016.
8 Q. You, "Sentiment and Emotion Analysis for Social Multimedia: Methodologies and Applications," Proceedings of the 2016 ACM on Multimedia Conference, pp. 1445-1449, 2016.
9 Q. You, J. Luo, H. Jin, and J. Yang, "Building a Large Scale Dataset for Image Emotion Recognition: The Fine Print and the Benchmark," Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, pp. 308-314, 2016.
10 J.M. Mang, and D.S. Kim, "Hume's Sentimental Aesthetics and the Principle of Sympathy," Philosophical Investigation, Vol. 38, No. 1, pp. 55-88, 2015.
11 T. Jacobsen, and L. Hofel, "Aesthetic Judgments of Novel Graphic Patterns: Analyses of Individual Judgments," Percept Mot Skills, Vol. 95, No. 3, pp. 755-66, 2002.   DOI
12 D.J. Freedman, M. Riesenhuber, T. Poggio, and E.K. Miller, “Categorical Representation of Visual Stimuli in the Primate Prefrontal Cortex,” Science, Vol. 291, No. 5502, pp. 312-316, 2001.   DOI
13 G. Bamossy, D.L. Scammon, and M. Johnston, "A Preliminary Investigation of the Reliability and Validity of an Aesthetic Judgment Test," Advances in Consumer Research, Vol. 10, No. 1, pp.685-690, 1983.
14 M. de Tommaso, C. Pecoraro, M. Sardaro, C. Serpino, G. Lancioni, and P. Livera, “Influence of Aesthetic Perception on Visual Event-related Potentials,” Consciousness and Cognition, Vol. 17, No. 3, pp. 933-945, 2008.   DOI
15 J.D. Mayer, M. DiPaolo, and P. Salovey, "Perceiving Affective Content in Ambiguous Visual Stimuli: A Component of Emotional Intelligence," Journal of Personality Assessment, Vol. 54, No. 3-4, pp. 772-781, 1990.   DOI
16 H. Kawasaki, R. Adolphs, O. Kaufman, H. Damasio, A.R. Damasio, M. Granner et al., “Single-neuron Responses to Emotional Visual Stimuli Recorded in Human Ventral Prefrontal Cortex,” Nature Neuroscience, Vol. 4, No. 1, pp. 15-16, 2001.   DOI
17 M.J. Lee, H.L. Kim, H.B. Kang, "EEG-based Analysis of Auditory Stimulations Generated from Watching Disgust-Eliciting Videos," Journal of Korea Multimedia Society, Vol. 19, No. 4, pp. 756-764, 2016.   DOI
18 N.N. Van Dongen, J.W. Van Strien, and K. Dijkstra, "Implicit Emotion Regulation in the Context of Viewing Artworks: ERP Evidence in Response to Pleasant and Unpleasant Pictures," Brain and Cognition, Vol. 107, pp. 48-54, 2016.   DOI
19 T. De Smedt, L. Menschaert, P. Heremans, L. Lechat, and G. Dhooghe, "An EEG Study of Creativity in Expert Classical Musicians," arXiv Preprint arXiv:1612.06719, 2016.
20 L.H. Chew, J. Teo, and J. Mountstephens, “Aesthetic Preference Recognition of 3D Shapes using EEG,” Cognitive Neurodynamics, Vol. 10, No. 2, pp. 165-173, 2016.   DOI
21 S. Caldenhove, L.G.J.M. Borghans, A. Blokland, A. Sambeth, "Role of Acetylcholine and Serotonin in Novelty Processing using an Oddball Paradigm," Behavioural Brain Research, Vol. 331, pp. 199-204, 2017.   DOI