Real-time 6-DoF Pose Estimation by an Event-based Camera using Active
  LED Markers
Gerald Ebmer Adam Loch Minh Nhat Vu Germain Haessig Roberto Mecca Markus Vincze Christian Hartl-Nesic Andreas Kugi
Real-time applications for autonomous operations depend largely on fast and
robust vision-based localization systems. Since image processing tasks require
processing large amounts of data, the computational resources often limit the
performance of other processes. To overcome this limitation, traditional
marker-based localization systems are widely used since they are easy to
integrate and achieve reliable accuracy. However, classical marker-based
localization systems significantly depend on standard cameras with low frame
rates, which often lack accuracy due to motion blur. In contrast, event-based
cameras provide high temporal resolution and a high dynamic range, which can be
utilized for fast localization tasks, even under challenging visual conditions.
This paper proposes a simple but effective event-based pose estimation system
using active LED markers (ALM) for fast and accurate pose estimation. The
proposed algorithm is able to operate in real time with a latency below
\SI{0.5}{\milli\second} while maintaining output rates of \SI{3}{\kilo \hertz}.
Experimental results in static and dynamic scenarios are presented to
demonstrate the performance of the proposed approach in terms of computational
speed and absolute accuracy, using the OptiTrack system as the basis for
measurement.