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Eye-Gaze-Based Intention Recognition for Selection Task by Using SVM-RF

  • Shuai Wang
  • , Hongwei Niu
  • , Wanni Wei
  • , Xiaonan Yang*
  • , Shuoyang Zhang
  • , Mingyu Ai
  • *此作品的通讯作者
  • Beijing Institute of Technology

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This paper focuses on the problem of intention recognition in eye-gaze-based interaction. The user’s intention could be divided into two types: selection and non-selection. In this study, a within-group experimental design was designed to complete the target letter selection task through eye-gaze-based interaction. Python is used to develop an experimental software for better flexibility in recording data. The SVM-RF model has been built and compared with other algorithms such as SVM, RF, etc. The importance weight of different eye movement behavior features on the accuracy of intention recognition has been analyzed by comparing the accuracy of the model through the permutation feature importance method. The results indicated that the SVM-RF model had a prediction accuracy of 94.3%, which can effectively predict the user’s selection intention and provides reference value for the future development of eye-gaze-based interaction technology.

源语言英语
主期刊名Human-Computer Interaction - Thematic Area, HCI 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Proceedings
编辑Masaaki Kurosu, Ayako Hashizume
出版商Springer Science and Business Media Deutschland GmbH
157-168
页数12
ISBN(印刷版)9783031604485
DOI
出版状态已出版 - 2024
活动Human Computer Interaction thematic area of the 26th International Conference on Human-Computer Interaction, HCII 2024 - Washington, 美国
期限: 29 6月 20244 7月 2024

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
14688 LNCS
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议Human Computer Interaction thematic area of the 26th International Conference on Human-Computer Interaction, HCII 2024
国家/地区美国
Washington
时期29/06/244/07/24

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