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Eye-Tracking Technologies
Theory, Methods and Applications
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This reprint gathers recent advances in eye-tracking technologies across theory, methods, and applications. It features contributions on core topics-gaze estimation, oculomotor measurement, event-camera-based pupil tracking, and area-of-interest analytics-alongside application-driven studies in transportation, human-computer interaction, vision science, and education. The articles demonstrate how improved sensors, computer vision, and neural networks are reshaping attention analysis, enabling reliable metrics in naturalistic environments and clinical settings. Collectively, the reprint highlights methodological rigor (from data quality to validation), practical deployment (from simulators to on-road and classroom contexts), and emerging trends such as deep learning pipelines and remote, video-based assessment. It is intended for researchers and practitioners seeking a clear view of the state of the art and the challenges ahead in building robust, interpretable, and ethically grounded eye-tracking solutions.
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