Event-based high-speed low-latency fiducial marker tracking

Abstract

Motion and dynamic environments, especially under challenging lighting conditions, are still an open issue in the field of computer vision. In this paper, we propose an online, end-to-end pipeline for real-time, low latency, 6 degrees-of-freedom pose estimation and tracking of fiducial markers. We employ the high-speed abilities of event-based sensors to directly refine spatial transformations. Furthermore, we introduce a novel two-way verification process for detecting tracking errors by backtracking the estimated pose, allowing to evaluate the quality of our tracking. This approach allows us to achieve pose estimation with an average latency lower than 3 ms and with an average error lower than 5 mm.