Flow-Based Visual-Inertial Odometry for Neuromorphic Vision Sensors Using non-Linear Optimization with Online Calibration

Mahmoud Khairallah, Abanob Soliman, Fabien Bonardi, David Roussel, Samia Bouchafa

2023

Abstract

Neuromorphic vision sensors (also known as event-based cameras) operate according to detected variations in the scene brightness intensity. Unlike conventional CCD/CMOS cameras, they provide information about the scene with a very high temporal resolution (in the order of microsecond) and high dynamic range (exceeding 120 dB). These mentioned capabilities of neuromorphic vision sensors induced their integration in various robotics applications such as visual odometry and SLAM. The way neuromorphic vision sensors trigger events is strongly coherent with the brightness constancy condition that describes optical flow. In this paper, we exploit optical flow information with the IMU readings to estimate a 6-DoF pose. Based on the proposed optical flow tracking method, we introduce an optimization scheme set up with a twist graph instead of a pose graph. Upon validation on high-quality simulated and real-world sequences, we show that our algorithm does not require any triangulation or key-frame selection and can be fine-tuned to meet real-time requirements according to the events’ frequency.

Paper Citation

in Harvard Style

Khairallah M., Soliman A., Bonardi F., Roussel D. and Bouchafa S. (2023). Flow-Based Visual-Inertial Odometry for Neuromorphic Vision Sensors Using non-Linear Optimization with Online Calibration. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP; ISBN 978-989-758-634-7, SciTePress, pages 963-973. DOI: 10.5220/0011660400003417

in Bibtex Style

@conference{visapp23,
author={Mahmoud Khairallah and Abanob Soliman and Fabien Bonardi and David Roussel and Samia Bouchafa},
title={Flow-Based Visual-Inertial Odometry for Neuromorphic Vision Sensors Using non-Linear Optimization with Online Calibration},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP},
year={2023},
pages={963-973},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011660400003417},
isbn={978-989-758-634-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 5: VISAPP
TI - Flow-Based Visual-Inertial Odometry for Neuromorphic Vision Sensors Using non-Linear Optimization with Online Calibration
SN - 978-989-758-634-7
AU - Khairallah M.
AU - Soliman A.
AU - Bonardi F.
AU - Roussel D.
AU - Bouchafa S.
PY - 2023
SP - 963
EP - 973
DO - 10.5220/0011660400003417
PB - SciTePress