How eye tracking works and why it matters

Eye tracking 101 series - #1

For more than two decades, Tobii has advanced the field of eye tracking, helping researchers and innovators understand how people look, think, and navigate the world. But before exploring what eye tracking can unlock, it’s helpful to understand how eye tracking technology actually works. From detecting subtle eye movements to interpreting gaze patterns in real time, here’s a clear look at the core mechanisms that make modern eye tracking possible.

How does eye tracking work

Eye tracking works by using sensors and light‑based technology to track eye movements and calculate where a person is looking. By mapping gaze over time, it reveals how people visually interact with screens or real‑world environments as they perform a task.

1. Illumination of the eyes: Tobii eye trackers use near-infrared light to illuminate the eyes, creating light reflection patterns on the pupil and cornea. This method, known as pupil-center corneal reflection (PCCR), helps estimate the point of gaze. 

2. Reflection detection by sensors: Camera sensors capture images of the eyes and reflections. Depending on the eye tracker speed, you can acquire detailed information about specific eye movements. For instance, Tobii Pro Spectrum captures images every 0.833 ms (1200Hz), allowing the tracking of microsaccades. 

3. Image processing and analysis: Advanced algorithms are employed to estimate a 3D model of the eye and determine its spatial position. The pupil center and corneal reflection are detected to facilitate precise calculation of the gaze point. 

The building blocks of eye tracking technology

Calibration: Aligning the system to the user

Eye tracking begins with calibration. During this step, the user follows a visual target so the eye tracker can learn how their unique eye characteristics relate to known points in the visual scene. This process establishes a reference that allows the system to accurately map gaze throughout the session. A good calibration is essential — it directly affects the quality and reliability of the data that follows.

How different eye tracker types measure gaze

All eye trackers follow the same fundamental principles, but how gaze is mapped depends on the device type. Screen‑based eye trackers calculate gaze relative to a fixed display, making them well suited for controlled environments and digital content. Wearable eye trackers, on the other hand, combine eye data with a scene camera to measure gaze within the real world, allowing users to move naturally while their visual attention is recorded in context.

Sampling rate: How often gaze is measured

The sampling rate, measured in hertz (Hz), describes how frequently the eye tracker records gaze data. A higher sampling rate captures more data points per second, making it possible to analyze fast eye movements with greater detail. Lower sampling rates are often sufficient for general attention and usability studies, while higher rates are used when fine‑grained temporal analysis is needed.

Accuracy vs. Precision: Understanding data quality

Two terms often used when discussing eye tracking performance are accuracy and precision. Accuracy refers to how close the measured gaze point is to where the user is actually looking, while precision describes how consistent those measurements are over time. High‑quality eye tracking data depends on both — accurate placement of gaze and stable, repeatable measurements.

Why use near-infrared light? 

Near-infrared light is invisible to the human eye, ensuring no discomfort or distraction. It provides stable illumination in various conditions, ensuring reliable and accurate eye tracking results. 

Screen-based eye trackers: Mounted on a desktop or laptop screen, these
eye trackers calculate the eye’s position and gaze point on the monitor. They are widely used in scientific research, gaming, and consumer research. 

Wearable eye trackers: Wearables are worn like regular glasses and have a front-facing camera that records what the user is looking at. They offer firsthand insights into real-world environments and are utilized in research, training, and assessment. 

Eye tracking in XR headsets: In XR headsets, eye tracking components include cameras and light sources. Machine-learning algorithms interpret the camera feed to generate real-time data points, such as pupil size and gaze vector, thereby enhancing user experience in healthcare, training, simulation, and other applications. 

Unlocking deeper understanding of behavior

Tobii's eye tracking technology offers a powerful tool for understanding human behavior and enhancing various applications. Whether it's enhancing virtual reality experiences, improving road safety, or advancing scientific research, eye tracking provides valuable insights.