LiMoSeg: Real-time Bird’s Eye View based LiDAR Motion Segmentation

Sambit Mohapatra, Mona Hodaei, Senthil Yogamani, Stefan Milz, Heinrich Gotzig, Martin Simon, Martin Simon, Hazem Rashed, Patrick Maeder

2022

Abstract

Moving object detection and segmentation is an essential task in the Autonomous Driving pipeline. Detecting and isolating static and moving components of a vehicle’s surroundings are particularly crucial in path planning and localization tasks. This paper proposes a novel real-time architecture for motion segmentation of Light Detection and Ranging (LiDAR) data. We use two successive scans of LiDAR data in 2D Bird’s Eye View (BEV) representation to perform pixel-wise classification as static or moving. Furthermore, we propose a novel data augmentation technique to reduce the significant class imbalance between static and moving objects. We achieve this by artificially synthesizing moving objects by cutting and pasting static vehicles. We demonstrate a low latency of 8 ms on a commonly used automotive embedded platform, namely Nvidia Jetson Xavier. To the best of our knowledge, this is the first work directly performing motion segmentation in LiDAR BEV space. We provide quantitative results on the challenging SemanticKITTI dataset, and qualitative results are provided in https://youtu.be/2aJ-cL8b0LI.

Paper Citation

in Harvard Style

Mohapatra S., Hodaei M., Yogamani S., Milz S., Gotzig H., Simon M., Rashed H. and Maeder P. (2022). LiMoSeg: Real-time Bird’s Eye View based LiDAR Motion Segmentation. In Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 5: VISAPP; ISBN 978-989-758-555-5, SciTePress, pages 828-835. DOI: 10.5220/0010866000003124

in Bibtex Style

@conference{visapp22,
author={Sambit Mohapatra and Mona Hodaei and Senthil Yogamani and Stefan Milz and Heinrich Gotzig and Martin Simon and Hazem Rashed and Patrick Maeder},
title={LiMoSeg: Real-time Bird’s Eye View based LiDAR Motion Segmentation},
booktitle={Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 5: VISAPP},
year={2022},
pages={828-835},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010866000003124},
isbn={978-989-758-555-5},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2022) - Volume 5: VISAPP
TI - LiMoSeg: Real-time Bird’s Eye View based LiDAR Motion Segmentation
SN - 978-989-758-555-5
AU - Mohapatra S.
AU - Hodaei M.
AU - Yogamani S.
AU - Milz S.
AU - Gotzig H.
AU - Simon M.
AU - Rashed H.
AU - Maeder P.
PY - 2022
SP - 828
EP - 835
DO - 10.5220/0010866000003124
PB - SciTePress