Ferns for area of interest free scanpath classification

Wolfgang Fuhl, Nora Castner, Thomas Kübler, Alexander Lotz, Wolfgang Rosenstiel, Enkelejda Kasneci

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

Scanpath classification can offer insight into the visual strategies of groups such as experts and novices. We propose to use random ferns in combination with saccade angle successions to compare scanpaths. One advantage of our method is that it does not require areas of interest to be computed or annotated. The conditional distribution in random ferns additionally allows for learning angle successions, which do not have to be entirely present in a scanpath. We evaluated our approach on two publicly available datasets and improved the classification accuracy by ≈ 10 and ≈ 20 percent.

Original languageEnglish
Title of host publicationProceedings - ETRA 2019
Subtitle of host publication2019 ACM Symposium On Eye Tracking Research and Applications
EditorsStephen N. Spencer
PublisherAssociation for Computing Machinery
ISBN (Electronic)9781450367097
DOIs
StatePublished - 25 Jun 2019
Externally publishedYes
Event11th ACM Symposium on Eye Tracking Research and Applications, ETRA 2019 - Denver, United States
Duration: 25 Jun 201928 Jun 2019

Publication series

NameEye Tracking Research and Applications Symposium (ETRA)

Conference

Conference11th ACM Symposium on Eye Tracking Research and Applications, ETRA 2019
Country/TerritoryUnited States
CityDenver
Period25/06/1928/06/19

Keywords

  • Eye tracking
  • Random ferns
  • Scanpath analysis

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