Using Variable Dwell Time to Accelerate Gaze-Based Web Browsing with Two-Step Selection

被引:19
作者
Chen, Zhaokang [1 ]
Shi, Bertram E. [1 ]
机构
[1] Hong Kong Univ Sci & Technol, Dept Elect & Comp Engn, Kowloon, Hong Kong, Peoples R China
关键词
Bayes methods; Browsers; Gaze tracking; Hidden Markov models; Human computer interface; Inference algorithms; BRAIN-COMPUTER-INTERFACE; EYE-MOVEMENTS; INPUT;
D O I
10.1080/10447318.2018.1452351
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In order to avoid the "Midas Touch" problem, gaze-based interfaces for selection often introduce a dwell time: a fixed amount of time the user must fixate upon an object before it is selected. Past interfaces have used a uniform dwell time across all objects. Here, we propose a gaze-based browser using a two-step selection policy with variable dwell time. In the first step, a command (e.g., "back" or "select") is chosen from a menu using a dwell time that is constant across the different commands. In the second step, if the "select" command is chosen, the user selects a hyperlink using a dwell time that varies between different hyperlinks. We assign shorter dwell times to more likely hyperlinks and longer dwell times to less likely hyperlinks. In order to infer the likelihood each hyperlink will be selected, we have developed a probabilistic model of natural gaze behavior while surfing the web. We have evaluated a number of heuristic and probabilistic methods for varying the dwell times using both simulation and experiment. Our results demonstrate that varying dwell time improves the user experience in comparison with fixed dwell time, resulting in fewer errors and increased speed. While all of the methods for varying dwell time resulted in improved performance, the probabilistic models yielded much greater gains than the simple heuristics. The best performing model reduces error rate by 50% compared to 100ms uniform dwell time while maintaining a similar response time. It reduces response time by 60% compared to 300ms uniform dwell time while maintaining a similar error rate.
引用
收藏
页码:240 / 255
页数:16
相关论文
共 31 条
  • [21] Attention and choice: A review on eye movements in decision making
    Orquin, Jacob L.
    Loose, Simone Mueller
    [J]. ACTA PSYCHOLOGICA, 2013, 144 (01) : 190 - 206
  • [22] Pi JM, 2017, C HUM SYST INTERACT, P251, DOI 10.1109/HSI.2017.8005041
  • [23] A TUTORIAL ON HIDDEN MARKOV-MODELS AND SELECTED APPLICATIONS IN SPEECH RECOGNITION
    RABINER, LR
    [J]. PROCEEDINGS OF THE IEEE, 1989, 77 (02) : 257 - 286
  • [24] Raiha K.-J., 2012, Proceedings of the SIGCHI conference on human factors in computing systems, P3001
  • [25] Eye movements in reading and information processing: 20 years of research
    Rayner, K
    [J]. PSYCHOLOGICAL BULLETIN, 1998, 124 (03) : 372 - 422
  • [26] Gaze dependant prefetching of web content to increase speed and comfort of web browsing
    Rozado, David
    El Shoghri, Ahmad
    Jurdak, Raja
    [J]. INTERNATIONAL JOURNAL OF HUMAN-COMPUTER STUDIES, 2015, 78 : 31 - 42
  • [27] Salvucci D. D., 2000, CHI 2000 Conference Proceedings. Conference on Human Factors in Computing Systems. CHI 2000. The Future is Here, P273, DOI 10.1145/332040.332444
  • [28] Salvucci D.D., 2000, P 2000 S EYE TRACK R, P71, DOI [DOI 10.1145/355017.355028, 10.1145/355017.355028]
  • [29] Gaze bias both reflects and influences preference
    Shimojo, S
    Simion, C
    Shimojo, E
    Scheier, C
    [J]. NATURE NEUROSCIENCE, 2003, 6 (12) : 1317 - 1322
  • [30] Wang HF, 2015, IEEE ENG MED BIO, P1476, DOI 10.1109/EMBC.2015.7318649