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

Adam Loch (Vortragende:r), Germain Haessig, Markus Vincze

Publikation: Beitrag in Buch oder TagungsbandVortrag mit Beitrag in TagungsbandBegutachtung

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.
OriginalspracheEnglisch
TitelProceedings of the Fifteenth International Conference on Machine Vision (ICMV 2022)
Redakteure/-innenWolfgang Osten, Dmitry P. Nikolaev, Jianhong (Jessica) Zhou
Band12701
DOIs
PublikationsstatusVeröffentlicht - 7 Juni 2023
VeranstaltungFifteenth International Conference on Machine Vision (ICMV 2022) - Rome, Rome, Italien
Dauer: 18 Nov. 202220 Nov. 2022

Konferenz

KonferenzFifteenth International Conference on Machine Vision (ICMV 2022)
KurztitelICMV 2022
Land/GebietItalien
StadtRome
Zeitraum18/11/2220/11/22

Research Field

  • High-Performance Vision Systems

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