• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Computer Engineering & Science

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An attention analysis method based
on EEG supervising face images

LIU Ji-wei1,SHI Yin-jia1,BAI Yu1,YAN Chao-wen2   

  1. (1.School of Automation,University of Science and Technology Beijing,Beijing 100083;
    2.School of Computer and Communication Engineering,University of Science and Technology Beijing,Beijing 100083,China)
     
  • Received:2016-04-18 Revised:2016-11-23 Online:2018-02-25 Published:2018-02-25

Abstract:

Using computer vision technology, aiming at intelligently analyzing the attention of people in the mission, through the acquisition and analysis of face image videos and corresponding EEG signals, a continuous facial image information corresponding to the EEG information sample library is established. Under the premise of using the EEG information to supervise the attention degree of facial images, a method that uses facial information to judge the attention degree is applied. According to the recognition results of SVM (Support Vector Machine) classifiers trained under multiple distributed samples, there is a correlation between facial information and its attention degree. Therefore, it is feasible to use facial images to analyze person’s attention in task, and it provides objective data for subsequent evaluation of condition monitoring.
 

Key words: face recognition, feature extraction, EEG supervising, feature classification, attention analysis