3D Mask-Based Shape Loss Function for LIDAR Data for Improved 3D Object Detection

R. Park, C. Lee

2023

Abstract

In this paper, we propose a 3D shape loss function for improved 3D object detection for LIDAR data. As the LiDAR (Light Detection And Ranging) sensor plays a key role in many autonomous driving techniques, 3D object detection using LiDAR data has become an important issue. Due to inaccurate height estimation, 3D object detection methods using LiDAR data produce false positive errors. We propose a new 3D shape loss function based on 3D masks for improved performance. To accurately estimate ground ROI areas, we first apply an adaptive ground ROI estimation method to accurately estimate ground ROIs and then use the shape loss function to reduce false positive errors. Experimental shows some promising results.

Paper Citation

in Harvard Style

Park R. and Lee C. (2023). 3D Mask-Based Shape Loss Function for LIDAR Data for Improved 3D Object Detection. In Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS, ISBN 978-989-758-652-1, SciTePress, pages 305-312. DOI: 10.5220/0011966800003479

in Bibtex Style

@conference{vehits23,
author={R. Park and C. Lee},
title={3D Mask-Based Shape Loss Function for LIDAR Data for Improved 3D Object Detection},
booktitle={Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,},
year={2023},
pages={305-312},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011966800003479},
isbn={978-989-758-652-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Conference on Vehicle Technology and Intelligent Transport Systems - Volume 1: VEHITS,
TI - 3D Mask-Based Shape Loss Function for LIDAR Data for Improved 3D Object Detection
SN - 978-989-758-652-1
AU - Park R.
AU - Lee C.
PY - 2023
SP - 305
EP - 312
DO - 10.5220/0011966800003479
PB - SciTePress