Valtakari, Niilo V., Hooge, Ignace T.C., Viktorsson, Charlotte, Nyström, Pär, Falck-Ytter, Terje, Hessels, Roy S., Leerstoel Kemner, Experimental Psychology (onderzoeksprogramma PF), Helmholtz Institute, Leerstoel Kenemans, Leerstoel Kemner, Experimental Psychology (onderzoeksprogramma PF), Helmholtz Institute, and Leerstoel Kenemans
There is a long history of interest in looking behavior during human interaction. With the advance of (wearable) video-based eye trackers, it has become possible to measure gaze during many different interactions, even in challenging situations, such as during interactions between young children and their caregivers. We outline the different types of eye-tracking setups that currently exist to investigate gaze during interaction. The setups differ mainly with regard to the nature of the eye-tracking signal (head- or world-centered) and the freedom of movement allowed for the participants (see Figure 1). These crucial, yet often overlooked features place constraints on the research questions that can be answered about human interaction. Furthermore, recent developments in machine learning have made available the measurement of gaze directly from video recordings, without the need for specialized eye-tracking hardware, widening the spectrum of possible eye-tracking setups. We discuss the link between type of eye-tracking setup and the research question being investigated, and end with a decision tree to help researchers judge the appropriateness of specific setups (see Figure 2).