Date: August 2022
Conference: European Conference on Eye MovementsAffiliation: iMotions
Authors: Divya Seernani, Amandine Grappe, Andrew Korepanov, Kåre Jensen, Kerstin Wolf, Jessica M. Wilson, Nadia Pedersen
Abstract
The iMotions webcam based eye tracking (WebET), combined with the hidden markov models (HMM) for fixations classification is a potential tool for applied human behaviour research and teaching eye-tracking to larger cohorts. The present study explores the feasibility of carrying out large scale, replicable research projects. To verify how relevant the iMotions WebET can be to applied research and teaching, a part of the Yarbus (1967) study was replicated with N=10 participants. In an online study, participants were shown ‘The Unexpected Visitor’ in four conditions in a repeated measures design, each one asking a different question of the participants. Individual scanpaths and aggregated heatmaps were used for exploratory analysis. As in the seminal work by Yarbus, the present study asked if WebET can be used to distinguish where people look based on the question asked. Areas of interest (AOIs) were marked and calculated in iMotions to understand best practices for quantifying data from webET. Results show that even with a small sample size, the iMotions WebET combined with the HMM fixation classification can accurately distinguish between scanpaths of different conditions. Larger, well-placed AOIs can give eye-tracking insights helpful in understanding top-down cognitive processing of participants in the present study.
