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Virtual Cursor Control Using Eye Tracking and Hand Gestures
Subject area: Science,Engineering and Technology · Area of research: Computer Vision and Human Computer Interaction
DOI: https://doi.org/10.64388/IREV9I11-1717694
Abstract
Human–Computer Interaction (HCI) has evolved significantly with the advancement of Artificial Intelligence and Computer Vision technologies. Traditional input devices such as mouse and touchpads require physical interaction, which may not be suitable for individuals with physical disabilities or in touchless environments. This paper presents a real-time Virtual Cursor Control system using eye tracking and hand gestures. The system uses a standard webcam to detect iris movement for cursor navigation and hand gestures for performing mouse operations such as clicking, scrolling, and dragging. Eye tracking is implemented using MediaPipe FaceMesh, while hand gesture recognition is achieved using MediaPipe Hands. The system eliminates the need for specialized hardware, making it cost-effective and accessible. Experimental results demonstrate high accuracy (up to 90–95% for gesture recognition and ~85–90% for eye tracking) with minimal latency, making it suitable for real-time applications in accessibility systems, healthcare environments, and touchless computing.
Keywords
Human Computer Interaction, Eye Tracking, Hand Gesture Recognition, Virtual Cursor, MediaPipe, Computer Vision, Artificial Intelligence, Touchless Systems
References
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[3] S. Mitra and T. Acharya, “Gesture Recognition: A Survey,” IEEE Transactions on Systems, Man, and Cybernetics, vol. 37, no. 3, pp. 311–324, 2007.
[4] D. Li and D. J. Parkhurst, “Open-Source Software for Real-Time Visible Pupil Tracking,” Proceedings of the ACM Symposium on Eye Tracking Research and Applications, pp. 125–128, 2006.
[5] R. Y. Wang and J. Popović, “Real-Time Hand-Tracking with a Color Glove,” ACM SIGGRAPH, pp. 63–72, 2009.
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[7] A. Kaushik and R. Jain, “Virtual Mouse Control Using Hand Gesture Recognition,” International Journal of Computer Applications, vol. 179, no. 12, pp. 20–25, 2021.
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How to cite this paper
@article{1717694,
author = {Sariya Anjum, Prithvik S Gowda, Somashekhar P S, Uday Gowda N S, Yashas P Gowda},
title = {Virtual Cursor Control Using Eye Tracking and Hand Gestures},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {11},
pages = {1595-1599},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1717694.pdf},
abstract = {Human–Computer Interaction (HCI) has evolved significantly with the advancement of Artificial Intelligence and Computer Vision technologies. Traditional input devices such as mouse and touchpads require physical interaction, which may not be suitable for individuals with physical disabilities or in touchless environments. This paper presents a real-time Virtual Cursor Control system using eye tracking and hand gestures. The system uses a standard webcam to detect iris movement for cursor navigation and hand gestures for performing mouse operations such as clicking, scrolling, and dragging. Eye tracking is implemented using MediaPipe FaceMesh, while hand gesture recognition is achieved using MediaPipe Hands. The system eliminates the need for specialized hardware, making it cost-effective and accessible. Experimental results demonstrate high accuracy (up to 90–95% for gesture recognition and ~85–90% for eye tracking) with minimal latency, making it suitable for real-time applications in accessibility systems, healthcare environments, and touchless computing.},
keywords = {Human Computer Interaction, Eye Tracking, Hand Gesture Recognition, Virtual Cursor, MediaPipe, Computer Vision, Artificial Intelligence, Touchless Systems},
month = {May},
doi = {https://doi.org/10.64388/IREV9I11-1717694}
}