Unsupervised clustering of EOG as a viable substitute for optical eye tracking

Nina Flad, Tatiana Fomina, Heinrich Bulthoff, Lewis L. Chuang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Eye-movements are typically measured with video cameras and image recognition algorithms. Unfortunately, these systems are susceptible to changes in illumination during measurements. Electrooculography (EOG) is another approach for measuring eye-movements that does not suffer from the same weakness. Here, we introduce and compare two methods that allow us to extract the dwells of our participants from EOG signals under presentation conditions that are too difficult for optical eye tracking. The first method is unsupervised and utilizes density-based clustering. The second method combines the optical eye-tracker’s methods to determine fixations and saccades with unsupervised clustering. Our results show that EOG can serve as a sufficiently precise and robust substitute for optical eye tracking, especially in studies with changing lighting conditions. Moreover, EOG can be recorded alongside electroencephalography (EEG) without additional effort.

Original languageEnglish
Title of host publicationEye Tracking and Visualization - Foundations, Techniques, and Applications, ETVIS 2015
PublisherSpringer Heidelberg
Pages151-167
Number of pages17
ISBN (Print)9783319470238
DOIs
Publication statusPublished - 2017
Externally publishedYes
Event1st Workshop on Eye Tracking and Visualization, ETVIS 2015 - [state] IL, United States
Duration: 2015 Oct 252015 Oct 25

Publication series

NameMathematics and Visualization
ISSN (Print)16123786
ISSN (Electronic)2197666X

Other

Other1st Workshop on Eye Tracking and Visualization, ETVIS 2015
CountryUnited States
City[state] IL
Period15/10/2515/10/25

ASJC Scopus subject areas

  • Modelling and Simulation
  • Geometry and Topology
  • Computer Graphics and Computer-Aided Design
  • Applied Mathematics

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  • Cite this

    Flad, N., Fomina, T., Bulthoff, H., & Chuang, L. L. (2017). Unsupervised clustering of EOG as a viable substitute for optical eye tracking. In Eye Tracking and Visualization - Foundations, Techniques, and Applications, ETVIS 2015 (pp. 151-167). (Mathematics and Visualization). Springer Heidelberg. https://doi.org/10.1007/978-3-319-47024-5_9