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 200Hz.

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

Simpsi, Andrea;Aspesi, Andrea;Mentasti, Simone;Matteucci, Matteo
2025-01-01

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 200Hz.
2025
Computer Vision – ECCV 2024 Workshops. ECCV 2024
9783031919886
9783031919893
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1292489
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