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May 16, 2026

Virtual Cursor Control Using Eye Tracking and Hand Gestures

Key Points

The aim is to develop a real-time virtual cursor control system using eye tracking and hand gestures to enhance accessibility.
Developed a system using eye tracking with MediaPipe FaceMesh and hand gesture recognition with MediaPipe Hands.
Used a standard webcam for real-time tracking and navigation of the cursor.
Evaluated the system's performance in terms of accuracy and latency.
Achieved up to 90–95% accuracy for hand gesture recognition and ~85–90% for eye tracking.
Demonstrated minimal latency suitable for real-time applications in various environments.
Provided a cost-effective solution without the need for specialized hardware.

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.

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