Gaze Pattern

Gaze pattern research investigates how eye movements reflect cognitive processes, attention, and interactions with the environment. Current research focuses on developing accurate and efficient gaze tracking methods using computer vision, machine learning (including transformers and convolutional neural networks), and novel data encoding techniques, often applied to diverse contexts like autism diagnosis, human-computer interaction, and even fake image detection. These advancements are improving the understanding of human behavior and cognition, with applications ranging from assistive technologies and medical diagnostics to enhancing human-robot interaction and improving user experience in virtual and augmented reality.