Event-based eye tracking for smart eyewear

This paper presents an innovative approach to gaze tracking in the context of smart eyewear, utilizing a fully event-based algorithm. Traditional gaze-tracking methods often rely on grayscale or infrared imaging, which can be computationally intensive and raise privacy concerns. Our research addresses these issues by developing an algorithm that exclusively uses data from event-based sensors, optimizing for the limited computational capabilities of smart eyewear. The system uses simple geometrical operations, enabling efficient real-time processing. Experimental results demonstrate the feasibility of this approach, offering a promising solution for gaze tracking in compact, computationally constrained devices. Despite certain limitations in accuracy due to optimization for efficiency, the research underscores the practicality of this approach for practical, privacy-conscious applications in smart eyewear technology.