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Eye-Tracking Technologies
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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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Keywords
- 3D TV
- A
- Adjustments
- aircraft maintenance
- Attention capture
- Attention trajectory
- Audio-assisted reading
- augmented reality
- Augmented reality 3D head-up display
- Autostereoscopic 3D display
- BVRT test
- Car drivers’ perception
- Color
- Computer vision
- contrast sensitivity
- Controlled driving study
- deep neural network
- depth
- Detection
- driving
- dynamic vision sensor
- event camera
- Expertise
- Eye detection
- Eye fixations
- eye tracking
- Eye tracking for attention analysis
- Eye-tracking
- Eyes-off-the-road
- gaze behavior
- Gaze detection
- Gaze patterns
- High contrast visual acuity
- HMI systems
- human-machine interaction
- LSTM neural network
- marker detection
- MATB-II
- N
- Naturalistic driving
- neural networks
- Optokinetic nystagmus
- Outdoor advertising
- Procedural documentation
- Progressive power lenses
- Pupil dilation
- Railway safety
- Reading comprehension
- Reading modality
- Recognition of dyslexia
- School-age children
- Simulation-based experiments
- situational awareness
- Stereoscopic displays
- System latency
- Task demands
- Task load
- text type
- Train driver’s behavior
- Virtual reality
Links
DOI: 10.3390/books978-3-7258-6048-7Editions