Webcam Eye Tracking Guide
Labvanced's webcam eye tracking runs directly in the browser using a participant's built-in or external webcam, with no additional hardware required, and has been validated against research-grade equipment (Kaduk et al., 2024). This guide covers everything involved in building a study around it: how your stimuli relate to eye tracking, the calibration settings you can choose from, setting eye tracking up within a task, recording and exporting gaze data, using shapes as areas of interest, and what the process looks like from a participant's side.
If you are connecting your own in-lab eye tracking hardware instead, see Eye Tracking in Labvanced for that option.
In this section
Presenting Stimuli in an Eye Tracking Task
Start here: how stimuli and objects relate to eye tracking, before you touch any settings.
How to Choose Eye Tracking Calibration Settings
A decision guide to calibration length, accuracy, and the Physiology Toolbox Version.
Setting Up Eye Tracking in a Task
Enable eye tracking for a task and configure recalibration, drift correction, and display mode.
Recording and Exporting Gaze Data
Build the events that capture gaze data, and read the resulting data export.
Using Shapes as Areas of Interest (AOI)
Tie specific stimulus objects to gaze and fixation measurements.
The Participant Calibration Experience
What calibration looks like from the participant's side, and how to help it go well.
Further Reading
Webcam Eye Tracking Technology
How Labvanced's webcam eye tracking technology works.
Webcam Eye Tracking Accuracy and Study Design
The evidence behind webcam eye tracking's validated accuracy, and the design decisions that affect it.
Eye Tracking in Labvanced
Considering in-lab hardware connected via LSL instead of webcam eye tracking? Start here.