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Screenshot of the calibration interface with the NonHumanPrimateCalController calibration controller class activated and calibrating a chimpanzee with a Tobii Pro TX300. This eye tracker does not support monocular calibration and does not provide eye images, hence the "change eye" and "eye images" buttons, as well as the eye images themselves, are not shown. Shown is the state during the calibration data collection stage of the procedure implemented by this controller, and data is being collected for target 7 (as indicated
Source publication
Accurate eye tracking is crucial for gaze-dependent research, but calibrating eye trackers in subjects who cannot follow instructions, such as human infants and nonhuman primates, presents a challenge. Traditional calibration methods rely on verbal instructions, which are ineffective for these populations. To address this, researchers often use att...
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Context 1
... data is collected successfully for that target, the video is shown at the next calibration target location, and the same logic for triggering data collection is used. Figure 5 shows the calibration phase of our procedure while data is being collected for the second calibration target. Once calibration data has been collected successfully for all targets (two per default), the procedure requests a calibration to be computed. ...
Citations
... Many tools exist for locally interfacing with eye trackers (e.g., Cornelissen et al., 2002;Dalmaijer et al., 2014;De Tommaso & Wykowska, 2019;Niehorster & Nyström, 2020, Niehorster et al., 2020a, 2024bsee Niehorster et al., 2025, for an overview). However, until now, there has not been an easy-to-use toolbox for streaming gaze data over the network, allowing straightforward implementation of networked eyetracking experiments. ...
Studying the behavior of multiple participants using networked eye-tracking setups is of increasing interest to researchers. However, to conduct such studies, researchers have had to create complicated ad hoc solutions for streaming gaze over a local network. Here we present TittaLSL, a toolbox that enables creating networked multi-participant experiments using Tobii eye trackers with minimal programming effort. An evaluation using 600-Hz gaze streams sent between 15 different eye-tracking stations revealed that the end-to-end latency, including the eye tracker’s gaze estimation processes, achieved by TittaLSL was 3.05 ms. This was only 0.10 ms longer than when gaze samples were received from a locally connected eye tracker. We think that these latencies are low enough that TittaLSL is suitable for the majority of networked eye-tracking experiments, even when the gaze needs to be shown in real time.
There is an abundance of commercial and open-source eye trackers available for researchers interested in gaze and eye movements. Which aspects should be considered when choosing an eye tracker? The paper describes what distinguishes different types of eye trackers, their suitability for different types of research questions, and highlights questions researchers should ask themselves to make an informed choice.
Researchers using eye tracking are heavily dependent on software and hardware tools to perform their studies, from recording eye tracking data and visualizing it, to processing and analyzing it. This article provides an overview of available tools for research using eye trackers and discusses considerations to make when choosing which tools to adopt for one’s study.
