论文阅读：A Slope-robust Cascaded Ground Segmentation in 3D Point Cloud for Autonomous Vehicles
论文名称：A Slope-robust Cascaded Ground Segmentation in 3D Point Cloud for Autonomous Vehicles 主要内容： 本文提出了一种从3D点云中将地面点和非地面点分开的方法，并且对于斜坡型地面点有很高的识别率。 方法主要分为两个步骤，受限利用激光雷达的物理特征（高度、角度）计算环间距，根据点实际间距与计算间距的比较初步去除
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相关文章
- 1. Ground Segmentation based on Loopy Belief Propagation for Sparse 3D Point Clouds （论文速读）
- 2. Fast Segmentation of 3D Point Clouds: A Paradigm on LiDAR Data for Autonomous Vehicle Applications阅读
- 3. 【论文整理】Point Cloud Dataset
- 4. 【3D 目标检测】2019 CVPR Learning 2D to 3D Lifting for Object Detection in 3D for Autonomous Vehicles
- 5. 【论文阅读】2017-Segmentation-Based Classification for 3D PointClouds in the Road Environment
- 6. Ground Estimation and Point Cloud Segmentation using SpatioTemporal Conditional Random Field（论文速读）
- 7. 【论文阅读】【综述】Deep Learning for 3D Point Clouds: A Survey
- 8. 论文《FLAME:Feature-Likeilhood Based Mapping and Localization for Autonomous Vehicles》阅读总结
- 9. 【论文阅读】PAIRWISE LINKAGE FOR POINT CLOUD SEGMENTATION-ISPRS-luxiaohu
- 10. 论文阅读：PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation