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Eye moving behaviors identification for gaze tracking interaction

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Abstract

The correct identification of eye moving behaviors is an important foundation for a gaze tracking interaction system. After analyzing the characteristics of eye moving behaviors in gaze tracking human computer interaction, a kind of eye moving behaviors classified method has been presented, in light of the fact that blinks, saccades, and fixations successively take place in certain sequences, and a blink is usually the beginning action or end action for a saccade or a fixation sequence. In addition, there are some other contributions in this paper. Firstly, a blink recognition algorithm has been proposed with eye’s height-width aspect ratio and iris or eyelid edge fitting curvature. Secondly, taking the recognized blink as a starting point to calculate the mean and standard deviation of eye’s moving displacements in a certain period, and then identifying the saccades and fixations in terms of the calculated parameters. At last, some experiments have been done, and the results show that the proposed method, by considering the relationship between eye behaviors, can accurately classify blinks, saccades, and fixations, especially for large-scale saccades and long time fixations. Moreover, the present also provides a new reference for designing an accessible interface to reduce the impacts on the reliability caused by the randomness of eye movements.

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Acknowledgments

This work was supported by National Natural Science Foundation of China (No. 61101177 and No. 51075252).

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Authors and Affiliations

  1. School of Mechatronics Engineering and Automation, Shanghai University, 27#, 149 Yanchang Rd., Shanghai, 200072, People’s Republic of China

    Qijie Zhao, Xinming Yuan, Dawei Tu & Jianxia Lu

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  1. Qijie Zhao
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  2. Xinming Yuan
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  3. Dawei Tu
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  4. Jianxia Lu
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Correspondence to Qijie Zhao.

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Zhao, Q., Yuan, X., Tu, D. et al. Eye moving behaviors identification for gaze tracking interaction. J Multimodal User Interfaces 9, 89–104 (2015). https://doi.org/10.1007/s12193-014-0171-2

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  • DOI: https://doi.org/10.1007/s12193-014-0171-2

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