Topology for gaze analyses - Raw data segmentation

  • Oliver Hein University Hamburg
  • Wolfgang H. Zangemeister Neurological University Clinic Hamburg
Keywords: gaze trajectory, event detection, topological data analysis (TDA), clustering, parameter-free classification, visual strategy, local scanpath, global scanpath

Abstract

Recent years have witnessed a remarkable growth in the way mathematics, informatics,
and computer science can process data. In disciplines such as machine learning,
pattern recognition, computer vision, computational neurology, molecular biology,
information retrieval, etc., many new methods have been developed to cope with the
ever increasing amount and complexity of the data. These new methods offer interesting
possibilities for processing, classifying and interpreting eye-tracking data. The
present paper exemplifies the application of topological arguments to improve the
evaluation of eye-tracking data. The task of classifying raw eye-tracking data into
saccades and fixations, with a single, simple as well as intuitive argument, described
as coherence of spacetime, is discussed, and the hierarchical ordering of the fixations
into dwells is shown. The method, namely identification by topological characteristics
(ITop), is parameter-free and needs no pre-processing and post-processing of the raw
data. The general and robust topological argument is easy to expand into complex
settings of higher visual tasks, making it possible to identify visual strategies.

As supplementary file an interactive demonstration of the method can be downloaded

Published
09-03-2017
How to Cite
Hein, O., & Zangemeister, W. (2017). Topology for gaze analyses - Raw data segmentation. Journal of Eye Movement Research, 10(1). https://doi.org/10.16910/jemr.10.1.1
Section
Articles