Webcam Eye-Tracking Browser Extension For General Navigation

Abstract

Webcam eye-tracking has emerged as a cost-effective alternative to traditional eye-tracking technologies, offering a promising solution for individuals with disabilities who face challenges in using standard input devices. In this study, the researchers developed a web browser extension leveraging webcam eye-tracking for web browsing and navigation. The extension was created using Webgazer.js, a webcam eye-tracking JavaScript library, and complemented by the development of four web applications optimized for webcam eye-tracking. Through user evaluations and testing, the system demonstrated encouraging results. Users found the system to be both useful and user-friendly, as evidenced by a progressive decline in error rates over time. This trend indicated successful iterative system improvements and increased user proficiency. Although variations in error rates were observed across different applications, suggesting varying levels of intuitiveness and user-friendliness, the overall findings affirmed the system’s utility and usability. This research achieved its objectives by effectively showcasing the extension’s potential as a robust tool for individuals with hand disabilities.