Comparison of eye movement filters used in HCI

ABSTRACT

We compared various real-time filters designed to denoise eye movements from low-sampling devices. Most of the filters found in literature were implemented and tested on data gathered in a previous study. An improvement was proposed for one of the filters. Parameters of each filter were adjusted to ensure their best performance. Four estimation parameters were proposed as criteria for comparison. The output from the filters was compared against two idealized signals (the signals denoised offline). The study revealed that FIR filters with triangular or Gaussian kernel (weighting) functions and parameters dependent on signal state show the best performance.

References

1. Duchowski, A, T. 2003 Eye Tracking Methodology: Theory and Practice. Springer-Verlag New York, Inc., Secaucus, NJ, USA.
2. Gu, J., Meng, M., Cook, A., and Faulkner, M. G. 2000. Analysis of eye tracking movements using FIR median hybrid filters. In Proceedings of the 2000 symposium on Eye tracking research & applications (ETRA '00), ACM, 65--69.
3. Jacob, R. J. K. 1993. Eye movement-based human-computer interaction techniques: Toward non-command interfaces. In Hartson, H. R. and Hix, D. (Eds.) Advances in Human-Computer Interaction 4, 151--190,
4. Jimenez, J., Gutierrez, D., and Latorre, P. 2008. Gaze-based Interaction for Virtual Environments. Granitzer, M. et al. (Eds.), Journal of Universal Computer Science 14, 19, 3085--3098.
5. van der Kamp, J., & Sundstedt, V. 2011. Gaze and Voice Controlled Drawing. In Proceeding of The 1st conference on Novel Gaze-Controlled Applications (NGCA'11), ACM, #9.
6. Kohler, M. 1997. Using the Kalman Filter to track Human Interactive Motion-Modelling and Initialization of the Kalman Filter for Translational Motion. Tech. Rep. #629, Informatik VII, University of Dortmund.
7. Komogortsev, O. V., & Khan, J. I. 2007. Kalman filtering in the design of eye-gaze-guided computer interfaces. In Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments (HCI'07), Springer-Verlag, 679--689.
8. Kumar, M., Klingner, J., Puranik, R., Winograd, T., and Paepcke. A. 2008. Improving the accuracy of gaze input for interaction. In Proceedings of the 2008 symposium on Eye tracking research & applications (ETRA '08), ACM, 65--68.
9. Nyström, M., & Holmqvist, K. 2010. An adaptive algorithm for fixation, saccade, and glissade detection in eyetracking data. Behavior Research Methods 42, 1, 188--204.
10. Olsson, P. 2007. Real-time and offline filters for eye tracking. Master's thesis, Royal Institute of Technology, Sweden.
11. Savitzky, A., & Golay, M. 1964. Smoothing and differentiation of data by simplified least squares procedures. Analytical chemistry 36, 8, 1627--1639
12. Sesin, A., Adjouadi, M., Cabrerizo, M., Ayala, M., and Barreto, A. 2008. Adaptive eye-gaze tracking using neural-network-based user profiles to assist people with motor disability. In Yuhasz, S. C. (Ed.), Journal of Rehabilitation Research & Development 45, 6, 801--818.
13. Stampe, D. M. 1993. Heuristic filtering and reliable calibration methods for video-based pupil-tracking systems. Behaviour Research Methods 25, 2, 137--142
14. Tole, J. R., and Young, L. R. 1981. Digital Filters for Saccade and Fixation Detection. In Fisher, D. F., Monty, R. A. and Senders, J. W. (Eds.) Eye Movements: Cognition and Visual Perception, Lawrence Erlbaum Associates, Hillsdale, NJ, 7--17.
15. Veneri, G., Federighi, P., Rosini, F., Federico, A., and Rufa, A. 2010. Influences of data filtering on human-computer interaction by gaze-contingent display and eye-tracking applications. Computers in Human Behaviour 26, 6, 1555--1563.
16. Zhang, X., Ren, X., and Zha. H. 2010. Modeling dwell-based eye pointing target acquisition. In Proceedings of the 28th international conference on Human factors in computing systems (CHI '10), ACM, 2083--2092.

Index Terms

• Human-centered computing

  • Human computer interaction (HCI)

    • HCI design and evaluation methods

    • Interaction devices

      • Touch screens