HeLiMOS：用于异构激光雷达传感器中移动物体分割的数据集
摘要
使用 3D 激光探测测距（LiDAR）传感器进行移动物体分割（MOS）对于场景理解和识别移动物体至关重要。尽管市场上提供了各种类型的 3D LiDAR 传感器，但 MOS 研究仍主要聚焦于来自机械旋转全向 LiDAR 传感器的 3D 点云。因此，我们缺乏针对扫描模式不规则的固态 LiDAR 传感器的 MOS 标签数据集。本文提出了一个标记数据集，称为 \textit{HeLiMOS}，用于测试来自四种异构 LiDAR 传感器（包括两种固态 LiDAR 传感器）的 MOS 方法。 Furthermore, we introduce a novel automatic labeling method to substantially reduce the labeling effort required from human annotators. To this end, our framework exploits an instance-aware static map building approach and tracking-based false label filtering. Finally, we provide experimental results regarding the performance of commonly used state-of-the-art MOS approaches on HeLiMOS that suggest a new direction for a sensor-agnostic MOS, which generally works regardless of the type of LiDAR sensors used to capture 3D point clouds. Our dataset is available at https://sites.google.com/view/helimos.
引用
@article{arxiv.2408.06328,
title = {HeLiMOS: A Dataset for Moving Object Segmentation in 3D Point Clouds From Heterogeneous LiDAR Sensors},
author = {Hyungtae Lim and Seoyeon Jang and Benedikt Mersch and Jens Behley and Hyun Myung and Cyrill Stachniss},
journal= {arXiv preprint arXiv:2408.06328},
year = {2024}
}
备注
Proc. IEEE/RSJ Int. Conf. Intell. Robot. Syst. (IROS) 2024