High-Frequency Near-Eye Ground Truth for Event-Based Eye Tracking

Andrea Simpsi, Andrea Aspesi, Simone Mentasti, Luca Merigo, Tommaso Ongarello, Matteo Matteucci

Abstract: Event-based eye tracking is a promising solution for efficient and low-power eye tracking in smart eyewear technologies. However, the novelty of event-based sensors has resulted in a limited number of available datasets, particularly those with eye-level annotations, crucial for algorithm validation and deep-learning training. This paper addresses this gap by presenting an improved version of a popular event-based eye-tracking dataset. We introduce a semi-automatic annotation pipeline specifically designed for event-based data annotation. Additionally, we provide the scientific community with the computed annotations for pupil detection at \(200\,\textrm{Hz}\).

External IDs:doi:10.1007/978-3-031-91989-3_19