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학술지 Extraction of User Preference for Video Stimuli Using EEG-Based User Responses
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저자
문진영, 김영래, 이형직, 배창석, 윤완철
발행일
201312
출처
ETRI Journal, v.35 no.6, pp.1105-1114
ISSN
1225-6463
출판사
한국전자통신연구원 (ETRI)
DOI
https://dx.doi.org/10.4218/etrij.13.0113.0194
협약과제
12SS1100, Connected Self: 라이프로그 정보와 스트림형 데이터 마이닝을 통한 건강 모니터링, 배창석
초록
Owing to the large number of video programs available, a method for accessing preferred videos efficiently through personalized video summaries and clips is needed. The automatic recognition of user states when viewing a video is essential for extracting meaningful video segments. Although there have been many studies on emotion recognition using various user responses, electroencephalogram (EEG)-based research on preference recognition of videos is at its very early stages. This paper proposes classification models based on linear and nonlinear classifiers using EEG features of band power (BP) values and asymmetry scores for four preference classes. As a result, the quadratic-discriminant-analysisbased model using BP features achieves a classification accuracy of 97.39% (짹0.73%), and the models based on the other nonlinear classifiers using the BP features achieve an accuracy of over 96%, which is superior to that of previous work only for binary preference classification. The result proves that the proposed approach is sufficient for employment in personalized video segmentation with high accuracy and classification power. © 2013 ETRI.
키워드
Brain-computer interface, Classification, EEG, Feature selection, Preference, Video
KSP 제안 키워드
Automatic recognition, Band Power, Brain computer interfaces(BCI), Classification models, EEG features, Early stages, Emotion recognition, Feature selection(FS), High accuracy, Linear and nonlinear, Personalized video