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1717694PublishedVol 9 · Issue 11

Virtual Cursor Control Using Eye Tracking and Hand Gestures

Sariya Anjum Prithvik S Gowda Somashekhar P S Uday Gowda N S Yashas P Gowda

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

How to cite this paper

Sariya Anjum, Prithvik S Gowda, Somashekhar P S, Uday Gowda N S, Yashas P Gowda "Virtual Cursor Control Using Eye Tracking and Hand Gestures" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 1595-1599 https://doi.org/10.64388/IREV9I11-1717694
Sariya Anjum, Prithvik S Gowda, Somashekhar P S, Uday Gowda N S, Yashas P Gowda "Virtual Cursor Control Using Eye Tracking and Hand Gestures" Iconic Research And Engineering Journals, vol. 9, no. 11, May. 2026, doi: https://doi.org/10.64388/IREV9I11-1717694
Sariya Anjum, Prithvik S Gowda, Somashekhar P S, Uday Gowda N S, Yashas P Gowda (2026). Virtual Cursor Control Using Eye Tracking and Hand Gestures. Iconic Research And Engineering Journals, 9(11). doi: https://doi.org/10.64388/IREV9I11-1717694
Sariya Anjum, Prithvik S Gowda, Somashekhar P S, Uday Gowda N S, Yashas P Gowda "Virtual Cursor Control Using Eye Tracking and Hand Gestures" Iconic Research And Engineering Journals, vol. 9, no. 11, May. 2026. Crossref, https://doi.org/10.64388/IREV9I11-1717694
@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}
  }