Visual Fatigue Assessment Based on Multi-task Learning
Wang, Danli; Wang, Xueyu; Song, Yaguang; Xing, Qian; Zheng, Nan
发表期刊JOURNAL OF IMAGING SCIENCE AND TECHNOLOGY
ISSN1062-3701
2019-11-01
卷号63期号:6页码:1-8
摘要

In recent years, with the rapid development of stereoscopic display technology, its applications have become increasingly popular in many fields, and, meanwhile, the number of audiences is also growing. The problem of visual fatigue is becoming more and more prominent. Visual fatigue is mainly caused by vergence-accommodation conflicts. An evaluation experiment was conducted, and the electroencephalogram (EEG) data of the subjects were collected when they were watching stereoscopic content, and then the stereoscopic fatigue state of the subjects during the viewing process was analyzed. As deep learning is proved to be an effective end-to-end learning method and multi-task learning can alleviate the problem of lacking annotated data, the authors establish a user visual fatigue assessment model based on EEG by using multi-task learning, which can effectively obtain the user's visual fatigue status, so as to make the comfort designs to avoid the harm caused by user's visual fatigue. (C) 2019 Society for Imaging Science and Technology.

DOI10.2352/J.ImagingSci.Technol.2019.63.6.060414
收录类别SCI
语种英语
资助项目National Natural Science Foundation of China[61872363] ; National Natural Science Foundation of China[61562063] ; National Natural Science Foundation of China[61272325] ; National Natural Science Foundation of China[61672507] ; National Key Research and Development Program[2016YFB0401202] ; National Natural Science Foundation of China[61501463] ; National Natural Science Foundation of China[61501463] ; National Key Research and Development Program[2016YFB0401202] ; National Natural Science Foundation of China[61672507] ; National Natural Science Foundation of China[61272325] ; National Natural Science Foundation of China[61562063] ; National Natural Science Foundation of China[61872363]
WOS研究方向Imaging Science & Photographic Technology
WOS类目Imaging Science & Photographic Technology
WOS记录号WOS:000508022200015
出版者I S & T-SOC IMAGING SCIENCE TECHNOLOGY
七大方向——子方向分类人工智能+科学
国重实验室规划方向分类AI For Science
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引用统计
被引频次:3[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/29538
专题复杂系统管理与控制国家重点实验室
通讯作者Wang, Danli
作者单位Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
第一作者单位中国科学院自动化研究所
通讯作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Wang, Danli,Wang, Xueyu,Song, Yaguang,et al. Visual Fatigue Assessment Based on Multi-task Learning[J]. JOURNAL OF IMAGING SCIENCE AND TECHNOLOGY,2019,63(6):1-8.
APA Wang, Danli,Wang, Xueyu,Song, Yaguang,Xing, Qian,&Zheng, Nan.(2019).Visual Fatigue Assessment Based on Multi-task Learning.JOURNAL OF IMAGING SCIENCE AND TECHNOLOGY,63(6),1-8.
MLA Wang, Danli,et al."Visual Fatigue Assessment Based on Multi-task Learning".JOURNAL OF IMAGING SCIENCE AND TECHNOLOGY 63.6(2019):1-8.
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