# Real-time 6-DoF Pose Estimation by an Event-based Camera using Active LED Markers

arXiv: https://arxiv.org/abs/2310.16618 · HTML: https://mlsanity.com/paper/2310.16618/

## Key facts

- Cited by 9 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 43 references that are in the map.
- First posted on arXiv 25 Oct 2023.

## Builds on (most cited first, 14 of 14)

- [Event-based Vision: A Survey](https://mlsanity.com/paper/1904.08405/) (2019)
- [ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM](https://mlsanity.com/paper/2007.11898/) (2020)
- [ORB-SLAM2: an Open-Source SLAM System for Monocular, Stereo and RGB-D Cameras](https://mlsanity.com/paper/1610.06475/) (2016)
- [Event-aided Direct Sparse Odometry](https://mlsanity.com/paper/2204.07640/) (2022)
- [Continuous-Time Visual-Inertial Odometry for Event Cameras](https://mlsanity.com/paper/1702.07389/) (2017)
- [Radio Localization and Mapping with Reconfigurable Intelligent Surfaces](https://mlsanity.com/paper/1912.09401/) (2019)
- [A State-of-the-Art Survey on Multidimensional Scaling Based Localization Techniques](https://mlsanity.com/paper/1906.03585/) (2019)
- [A Neuromorphic Vision-Based Measurement for Robust Relative Localization in Future Space Exploration Missions](https://mlsanity.com/paper/2206.11541/) (2022)
- [Machine Learning-based Framework for Optimally Solving the Analytical Inverse Kinematics for Redundant Manipulators](https://mlsanity.com/paper/2211.04275/) (2022)
- [Singularity Avoidance with Application to Online Trajectory Optimization for Serial Manipulators](https://mlsanity.com/paper/2211.02516/) (2022)
- [STag: A Stable Fiducial Marker System](https://mlsanity.com/paper/1707.06292/) (2017)
- [GSLAM: A General SLAM Framework and Benchmark](https://mlsanity.com/paper/1902.07995/) (2019)
- [Sampling-Based Trajectory (re)planning for Differentially Flat Systems: Application to a 3D Gantry Crane](https://mlsanity.com/paper/2209.05573/) (2022)
- [Two-Step Online Trajectory Planning of a Quadcopter in Indoor Environments with Obstacles](https://mlsanity.com/paper/2211.06377/) (2022)

## Built on by (most cited first, 9 of 9)

- [MTevent: A Multi-Task Event Camera Dataset for 6D Pose Estimation and Moving Object Detection](https://mlsanity.com/paper/2505.11282/) (2025)
- [A Monocular Event-Camera Motion Capture System](https://mlsanity.com/paper/2502.12113/) (2025)
- [Low-Latency Event-Based Velocimetry for Quadrotor Control in a Narrow Pipe](https://mlsanity.com/paper/2507.15444/) (2025)
- [Event6D: Event-based Novel Object 6D Pose Tracking](https://mlsanity.com/paper/2603.28045/) (2026)
- [E-VLC: A Real-World Dataset for Event-based Visible Light Communication And Localization](https://mlsanity.com/paper/2504.18521/) (2025)
- [Event-based Optical Marker Systems: A survey](https://mlsanity.com/paper/2504.20736/) (2025)
- [Towards agile multi-robot systems in the real world: Fast onboard tracking of active blinking markers for relative localization](https://mlsanity.com/paper/2502.01172/) (2025)
- [A Height-Constrained 2-Point Minimal Solver for Pose Estimation from Active LED Markers with Event Cameras](https://mlsanity.com/paper/2608.09520/) (2026)
- [Asynchronous Tracking, Optical Communication and 3D Motion Capture using Event-based Sensors](https://mlsanity.com/paper/2610.04342/) (2026)

## Abstract (arXiv)

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 SI0.5millisecond while maintaining output rates of SI3kilo 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.