Real-time eye gaze tracking with an unmodified commodity webcam employing a neural network
Abstract
An eye-gaze-guided computer interface could enable computer use by the seriously disabled but existing systems cost tens of thousands of dollars or have cumbersome setups. This paper presents a methodology for real-time eye gaze tracking using a standard webcam without the need for hardware modification or special placement. An artificial neural network was employed to estimate the location of the user's gaze based on an image of the user's eye, mimicking the way that humans determine where another person is looking. Accuracy measurements and usability experiments were performed using a laptop computer with a webcam built into the screen. The results show this approach to be promising for the development of usable eye tracking systems using standard webcams, particularly those built into many laptop computers.
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The rise of real-time eye gaze tracking with regular webcams points to a new possible way of assessing human reliance on AI in assisted decision-making for a wider range of everyday situations.
“The rise of real-time eye gaze tracking with regular webcams [55,56,69] points to a new possible way of assessing human reliance on AI in assisted decisionmaking for a wider range of everyday situations.”
From Understanding User Reliance on AI in Assisted Decision-Making (2022) · cites this paper as [69]
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References 8 · Cited by 136
- Authors
- Sewell, W., & Komogortsev, O.
- Affiliations
- Texas State University (US)
- ORCID
- Komogortsev, Oleg
- Venue
- CHI '10 Extended Abstracts on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2010-04-10
- Pages
- 3739-3744
- OpenAlex
- W2123000084
- Cited by
- 136
- References
- 8
- Citations by year
- 2026: 3 · 2025: 5 · 2024: 7 · 2023: 8 · 2022: 8 · 2021: 8 · 2020: 14 · 2019: 21 · 2018: 8 · 2017: 12 · 2016: 9 · 2015: 9 · 2014: 9 · 2013: 6 · 2012: 4
- FWCI
- 3.67
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Gaze Tracking and Assistive Technology
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Visual Attention and Saliency Detection
- Keywords
- eye gaze tracking, webcam-based eye tracking, artificial neural networks, gaze estimation, eye image analysis, assistive technology, usability
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