摘要
利用计算机视觉技术智能分析处于任务中的人的专注度问题。通过对人脸图像视频和对应脑电信号的采集和分析处理,建立连续的面部图片对应脑电信息的样本库,提出一种在脑电信息监督面部图片专注度的前提下,使用人的面部信息分析其专注度的方法。根据在多分布样本下训练的支持向量机分类器的识别结果,面部信息与其专注度确实存在相关关系,所以利用人脸图片分析任务中人的专注度是可行性的,并为后续的状态分析提供客观数据。
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.
出处
《计算机工程与科学》
CSCD
北大核心
2018年第2期298-303,共6页
Computer Engineering & Science
基金
北京科技大学教学改革与研究项目(Grant JG2014Z06)
关键词
人脸识别
特征提取
脑电信息监督
特征分类
专注度分析
face recognition
feature extraction
EEG supervising
feature classification
attention analysis
