Eye Tracking

Eye tracking uses cameras and other sensors to estimate gaze direction and characterize movements such as fixations and saccades, revealing how people explore visual information. Methods include geometric pupil-and-glint models, appearance-based deep learning, temporal sequence models, and calibration or synthetic-data techniques for adapting systems to users and devices. Applications range from reading, visual search, and clinical assessment to driving, robotics, and interactive displays. A central challenge is making systems accurate beyond controlled settings, where lighting, motion, device placement, and individual differences increase error and calibration demands; behavioral or clinical conclusions also require careful validation.