Eye-tracking based adaptive user interface: implicit human-computer interaction for preference indication

被引:25
|
作者
Cheng, Shiwei [1 ]
Liu, Ying [2 ]
机构
[1] Zhejiang Univ Technol, Coll Comp Sci & Technol, Hangzhou 310023, Zhejiang, Peoples R China
[2] Nokia Res Ctr, Beijing, Peoples R China
关键词
Eye-tracking; Adaptive user interface; Preference inference; Human-computer interaction;
D O I
10.1007/s12193-011-0064-6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we proposed and evaluated an adaptive recommendation system based on users' eye-tracking data and an optimization algorithm called IGA. An eye tracker was utilized to acquire users' eye movement data and extract three measures, which were respectively number of fixation, fixation duration and the first fixation on target item. Based on the results on the three measures, we inferred users' preferences and adjusted the user interfaces based on users' preferences. We developed a prototype system, which could adaptively recommend digital cameras to users. Then we conducted a user study with the prototype system and found that participants could identify their preferred products with a comparatively less time period and higher satisfaction.
引用
收藏
页码:77 / 84
页数:8
相关论文
共 50 条
  • [1] Eye-tracking based adaptive user interface: implicit human-computer interaction for preference indication
    Shiwei Cheng
    Ying Liu
    [J]. Journal on Multimodal User Interfaces, 2012, 5 : 77 - 84
  • [2] Vision assistant: a human-computer interface based on adaptive eye-tracking
    Hardzeyeu, V.
    Klefenz, F.
    Schikowski, P.
    [J]. DESIGN AND NATURE III: COMPARING DESIGN IN NATURE WITH SCIENCE AND ENGINEERING, 2006, 87 : 175 - +
  • [3] Navigation Through Eye-Tracking for Human-Computer Interface
    Pavani, M. Lakshmi
    Prakash, A. V. Bhanu
    Koushik, M. S. Shwetha
    Amudha, J.
    Jyotsna, C.
    [J]. INFORMATION AND COMMUNICATION TECHNOLOGY FOR INTELLIGENT SYSTEMS, ICTIS 2018, VOL 2, 2019, 107 : 575 - 586
  • [4] Cognitive evaluation based on regression and eye-tracking for layout on human-computer multi-interface
    Wang, Linlin
    Tang, Wenzhe
    Montagu, Enid
    Wu, Xiaoli
    Xue, Chengqi
    [J]. BEHAVIOUR & INFORMATION TECHNOLOGY, 2024,
  • [5] An integrated neural network model for eye-tracking during human-computer interaction
    Wang, Li
    Wang, Changyuan
    Zhang, Yu
    Gao, Lina
    [J]. MATHEMATICAL BIOSCIENCES AND ENGINEERING, 2023, 20 (08) : 13974 - 13988
  • [6] AI-Based Eye Tracking for Human-Computer Interaction
    Crespo, David Sancho
    Yu, Xinrui
    Saniie, Jafar
    [J]. 2024 IEEE INTERNATIONAL CONFERENCE ON ELECTRO INFORMATION TECHNOLOGY, EIT 2024, 2024, : 241 - 246
  • [7] A training and assessment system for human-computer interaction combining fNIRS and eye-tracking data
    Qu, Jing
    Bu, Lingguo
    Zhao, Lei
    Wang, Yonghui
    [J]. ADVANCED ENGINEERING INFORMATICS, 2024, 62
  • [8] Methods of Control Improvement in an Eye Tracking Based Human-Computer Interface
    Bozomitu, R. G.
    Pasarica, A.
    Cehan, V.
    Rotariu, C.
    Costin, H.
    [J]. 2017 IEEE 23RD INTERNATIONAL SYMPOSIUM FOR DESIGN AND TECHNOLOGY IN ELECTRONIC PACKAGING (SIITME), 2017, : 300 - 303
  • [9] Human-Computer Interface based on Eye Tracking with Dwell Time Selection
    Pasarica, Alexandru
    Bozomitu, Radu Gabriel
    Costin, Hariton
    Miron, Casian
    Rotariu, Cristian
    [J]. 2017 IEEE 23RD INTERNATIONAL SYMPOSIUM FOR DESIGN AND TECHNOLOGY IN ELECTRONIC PACKAGING (SIITME), 2017, : 375 - 378
  • [10] Eye Tracking Based Control System for Natural Human-Computer Interaction
    Zhang, Xuebai
    Liu, Xiaolong
    Yuan, Shyan-Ming
    Lin, Shu-Fan
    [J]. COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2017, 2017