Low Latency Pedestrian Detection Based on Dynamic Vision Sensor and RGB Camera Fusion

Bingyu Huang, Gianni Allebosch, Peter Veelaert, Tim Willems, Wilfried Philips, Jan Aelterman

2025

Abstract

Advanced driver assistance systems currently adopt RGB cameras as visual perception sensors, which rely primarily on static features and are limited in capturing dynamic changes due to fixed frame rates and motion blur. A very promising sensor alternative is the dynamic vision sensor(DVS) with microsecond temporal resolution that records an asynchronous stream of per-pixel brightness changes, also known as event stream. However, in autonomous driving scenarios, it’s challenging to distinguish between events caused by the vehicle’s motion and events caused by actual moving objects in the environment. To address this, we design a motion segmentation algorithm based on epipolar geometry and apply it to DVS data, effectively removing static background events and focusing solely on dynamic objects. Furthermore, we propose a system that fuses the dynamic information captured by event cameras and rich appearance details from RGB cameras. Experiments show that our proposed method can effectively improve detection performance while showing great potential in decision latency.

Paper Citation

in Harvard Style

Huang B., Allebosch G., Veelaert P., Willems T., Philips W. and Aelterman J. (2025). Low Latency Pedestrian Detection Based on Dynamic Vision Sensor and RGB Camera Fusion. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP; ISBN 978-989-758-728-3, SciTePress, pages 841-850. DOI: 10.5220/0013126600003912

in Bibtex Style

@conference{visapp25,
author={Bingyu Huang and Gianni Allebosch and Peter Veelaert and Tim Willems and Wilfried Philips and Jan Aelterman},
title={Low Latency Pedestrian Detection Based on Dynamic Vision Sensor and RGB Camera Fusion},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP},
year={2025},
pages={841-850},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013126600003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 2: VISAPP
TI - Low Latency Pedestrian Detection Based on Dynamic Vision Sensor and RGB Camera Fusion
SN - 978-989-758-728-3
AU - Huang B.
AU - Allebosch G.
AU - Veelaert P.
AU - Willems T.
AU - Philips W.
AU - Aelterman J.
PY - 2025
SP - 841
EP - 850
DO - 10.5220/0013126600003912
PB - SciTePress