Introduction to Eye Tracking: A Hands-On Tutorial for Students and Practitioners
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Abstract (arXiv)
Eye-tracking technology is widely used in various application areas such as psychology, neuroscience, marketing, and human-computer interaction, as it is a valuable tool for understanding how people process information and interact with their environment. This tutorial provides a comprehensive introduction to eye tracking, from the basics of eye anatomy and physiology to the principles and applications of different eye-tracking systems. The guide is designed to provide a hands-on learning experience for everyone interested in working with eye-tracking technology. Therefore, we include practical case studies to teach students and professionals how to effectively set up and operate an eye-tracking system. The tutorial covers a variety of eye-tracking systems, calibration techniques, data collection, and analysis methods, including fixations, saccades, pupil diameter, and visual scan path analysis. In addition, we emphasize the importance of considering ethical aspects when conducting eye-tracking research and experiments, especially informed consent and participant privacy. We aim to give the reader a solid understanding of basic eye-tracking principles and the practical skills needed to conduct their experiments. Python-based code snippets and illustrative examples are included in the tutorials and can be downloaded at: https://gitlab.lrz.de/hctl/Eye-Tracking-Tutorial.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Apr 2024.
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Citing papers per year: 2025: 4; 2026: 1.
5 papers.
- 2025Exploring Context-aware and LLM-driven Locomotion for Immersive Virtual Realitycited by 1
- 2025Examining the Role of LLM-Driven Interactions on Attention and Cognitive Engagement in Virtual Classroomscited by 1
- 2025Multimodal Behavioral Patterns Analysis with Eye-Tracking and LLM-Based Reasoningcited by 1
- 2025HAGI++: Head-Assisted Gaze Imputation and Generationcited by 0
- 2026Safeguarding Privacy: Privacy-Preserving Detection of Mind Wandering and Disengagement Using Federated Learning in Online Educationcited by 0
- 2026Safeguarding Privacy: Privacy-Preserving Detection of Mind Wandering and Disengagement Using Federated Learning in Online Education10 Feb 2026
- 2025HAGI++: Head-Assisted Gaze Imputation and Generation4 Nov 2025
- 2025Multimodal Behavioral Patterns Analysis with Eye-Tracking and LLM-Based Reasoning24 Jul 2025
- 2025Examining the Role of LLM-Driven Interactions on Attention and Cognitive Engagement in Virtual Classrooms12 May 2025
- 2025Exploring Context-aware and LLM-driven Locomotion for Immersive Virtual Reality24 Apr 2025