Gaze tracking is the use of cameras, sensors, and algorithms to estimate where a person is looking. In human-computer interaction, that can support hands-free navigation, dwell-based selection, reading analysis, attention measurement, and interface adaptation based on where the user's visual focus appears to be.
How It Works
Some gaze-tracking systems use specialized hardware, while newer systems can work with standard front-facing cameras and on-device models. The output is rarely perfect intent. A system may know where the user is looking, but not why. That is why strong gaze interfaces often pair eye tracking with dwell timing, larger targets, fallback controls, and other signals that help reduce accidental activation.
Why It Matters
Gaze tracking matters because it can reduce pointing effort, enable hands-free access, and reveal visual attention patterns that help interfaces become easier to use. It is especially important in accessibility, assistive technology, and adaptive layouts where the system can enlarge or prioritize targets near the user's focus.
Limits and Cautions
Gaze is useful, but it is not the same as deliberate choice. People look around, scan, and hesitate. Lighting, camera position, fatigue, glasses, and movement can all change tracking quality. Gaze data can also be sensitive, which is why privacy, consent, and local processing matter when teams use it in real products.
Related Yenra articles: Adaptive User Interfaces, Cognitive Assistance for Disabilities, Brain-Computer Interfaces (BCI), Virtual Reality Training, and Workload Detection in Human Factors Engineering.
Related concepts: Digital Accessibility, Computer Vision, Multimodal Learning, Sensor Fusion, and Human in the Loop.