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

Shuai Wang, Hongwei Niu, Wanni Wei, Xiaonan Yang*, Shuoyang Zhang, Mingyu Ai

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationHuman-Computer Interaction - Thematic Area, HCI 2024, Held as Part of the 26th HCI International Conference, HCII 2024, Proceedings
EditorsMasaaki Kurosu, Ayako Hashizume
PublisherSpringer Science and Business Media Deutschland GmbH
Pages157-168
Number of pages12
ISBN (Print)9783031604485
DOIs
Publication statusPublished - 2024
EventHuman Computer Interaction thematic area of the 26th International Conference on Human-Computer Interaction, HCII 2024 - Washington, United States
Duration: 29 Jun 20244 Jul 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14688 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceHuman Computer Interaction thematic area of the 26th International Conference on Human-Computer Interaction, HCII 2024
Country/TerritoryUnited States
CityWashington
Period29/06/244/07/24

Keywords

  • RF
  • SVM
  • eye-gaze-based interaction
  • intention recognition
  • selection task

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