The system first captures eye images under infrared illumination. Image analysis identifies the pupil and the corneal reflection, a light-related feature on the eye’s surface. Their positions provide the visual information needed to estimate gaze direction relative to a display or scene. This converts recorded eye features into measures of looking behavior.
Using both features provides complementary image landmarks for estimating gaze. Their relationship connects the observed appearance of the eye with the direction in which a person is looking, rather than treating one visible feature as the entire signal. The resulting estimate can then be examined alongside fixations and broader patterns of eye movement.
A fixation indicates where gaze is held, whereas eye movements describe changes in gaze across time. Considering both measures can show not only which display region or scene element attracted attention, but also how visual scanning progressed during reading, decision-making, or exposure to other environmental or digital stimuli.
A camera-based device, infrared illumination, and image-analysis capability form the core setup. The system observes the eyes while a person views a display or scene, then relates detected pupil and corneal-reflection positions to that visual context. This arrangement supports measurement in either laboratory settings or more natural viewing situations.
Laboratory settings support observation of responses to presented displays, while natural settings allow visual behavior to be examined in less restricted surroundings. Because the approach does not require physical contact, investigators can study attention, visual scanning, and responses to environmental or digital stimuli across different behavioral contexts.
The measurements can support studies of attention, reading, decision-making, and visual scanning, while also revealing responses to environmental or digital stimuli. In psychology, neuroscience, and education, they provide behavioral indicators of information processing. In usability research and human-computer interaction, the same measures help examine how people visually engage with digital interfaces.