Online recognition of fixations, saccades, and smooth pursuits for automated analysis of traffic hazard perception

Enkelejda Kasneci, Gjergji Kasneci, Thomas C. Kübler, Wolfgang Rosenstiel

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

39 Scopus citations

Abstract

Complex and hazardous driving situations often arise with the delayed perception of traffic objects. To automatically detect whether such objects have been perceived by the driver, there is a need for techniques that can reliably recognize whether the driver's eyes have fixated or are pursuing the hazardous object. A prerequisite for such techniques is the reliable recognition of fixations, saccades, and smooth pursuits from raw eye tracking data. This chapter addresses the challenge of analyzing the driver's visual behavior in an adaptive and online fashion to automatically distinguish between fixation clusters, saccades, and smooth pursuits.

Original languageEnglish
Title of host publicationArtificial Neural Networks - Methods and Applications in Bio-/Neuroinformatics
PublisherSpringer Verlag
Pages411-434
Number of pages24
ISBN (Print)9783319099026
DOIs
StatePublished - 2015
Externally publishedYes
Event23rd International Conference on Artificial Neural Networks, ICANN 2013 - Sofia, Bulgaria
Duration: 10 Sep 201313 Sep 2013

Publication series

NameArtificial Neural Networks - Methods and Applications in Bio-/Neuroinformatics

Conference

Conference23rd International Conference on Artificial Neural Networks, ICANN 2013
Country/TerritoryBulgaria
CitySofia
Period10/09/1313/09/13

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