Computer Cursor Control Using Eye and Face Gestures

Abstract

This research paper explores the design, implementation, and application of a hands-free computer cursor control system that utilizes eye and face gestures. The conventional use of a mouse or touchpad presents significant accessibility barriers for individuals with physical disabilities, motor impairments, or repetitive strain injuries. This study proposes and analyzes a solution that leverages a standard webcam and advanced computer vision algorithms to track eye and facial movements in real-time. By mapping head movements and gaze direction to cursor position and interpreting facial expressions like blinks, winks, or mouth movements for mouse clicks and commands, the system offers a natural and intuitive alternative for human-computer interaction. The paper discusses the core methodologies, including feature detection and machine learning models, and evaluates the system's potential to enhance accessibility, productivity, and usability, while also addressing inherent challenges such as accuracy, latency, and environmental dependencies.