3D localization using lensless event sensors for fast-moving objects

Abstract

A novel event sensor-based object localization method is proposed in this paper. It addresses the accuracy limitations of event sensors caused by their limited spatial resolution and binary grayscale levels. The method uses flickering beacons and replaces the event camera's lens with a mask printed with a marker field. This configuration distributes location-coded events across the entire sensor instead of confining them to a small region, as in traditional methods. Major algorithms, including pattern simulation and optimized matching, are designed to achieve 3D localization and pose estimation. Experiments show a 17.3% accuracy improvement over state-of-the-art event-based methods in average translation error, consistent across varying distances and angles. This demonstrates its suitability for surgical navigation, virtual reality, and other precise, real-time localization tasks.