Together with Ignace Hooge, Diederick Niehorster, Gabriel Diaz, Andrew Duchowski, and Jeff Pelz, I organised a symposium at the 2019 European Conference on Eye Movements in Alicante. The symposium has been published online by the Journal of Eye Movement Research.
Over the past years, we have used a self-built (by Tim Cornelissen) dual eye-tracking setup in our lab to investigate eye movements during dyadic interaction. Through a recent grant, we have had an updated version constructed by a professional constructor. The setup is back in a nice black metal look:
Here is a short example of the videos and eye-tracking data recorded using this setup:
In order to map eye-tracking data recorded at one side of the dual eye-tracking setup unto the video recorded at the other end, we use an automatic Area-of-Interest construction method based on Voronoi Tesselation and OpenFace facial landmark detection. It is freely available at the OpenScienceFramework.
The method is validated in: Hessels, R. S., Benjamins, J. S., Cornelissen, T. H. W., & Hooge, I. T. C. (2018). A Validation of Automatically-Generated Areas-of-Interest in Videos of a Face for Eye-Tracking Research. Frontiers in Psychology, 9(1367), 1–8. http://doi.org/10.3389/fpsyg.2018.01367
I’ve been involved in many eye-tracking studies with infants and young children as the participant group. While eye tracking can provide valuable insights into (cognitive) development, eye-tracking data obtained from infants and children are generally of lower quality as compared with eye-tracking data from adults. This is in part due to the fact that infants are difficult to restrain in their movement. I’ve been involved in two eye-tracker tests in which we compared eye trackers on their robustness to movement (view the first and the second here). Moreover, I’ve developed a fixation-classification algorithm that is specifically built for eye-tracking data of low quality. The software is freely available from GitHub.