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English(EN) ACZ-GSeg: Adaptive Concentric Zone-based Two-stage Ground Segmentation for LiDAR Point Clouds

新的激光雷达地面分割方法提高了自动导航精度

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了一种新颖的两阶段激光雷达数据地面点分割方法ACZ-GSeg。该方法利用自适应同心区域模型动态调整扇区划分，在局部区域内创建更均衡的点分布。该方法结合了最低高度种子约束和高度衰减加权进行初始地面候选提取，然后使用反射率强度一致性约束来优化不确定的点。ACZ-GSeg在基准数据集上展示了高精度和高召回率，能有效处理稀疏的远程点云和复杂的道路场景。 AI

排序理由 该集群包含一篇详细介绍激光雷达点云处理新方法的论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.CV 阅读 →

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新的激光雷达地面分割方法提高了自动导航精度

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该集群包含一篇详细介绍激光雷达点云处理新方法的论文。[lever_c_demoted from research: ic=1 ai=0.7]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Ge Zhang Chunyang Wang Bin Liu ·

    ACZ-GSeg：基于自适应同心区域的两阶段LiDAR点云地面分割

    arXiv:2607.12110v1 Announce Type: new Abstract: Ground segmentation is a fundamental prerequisite for autonomous navigation, environmental perception, and object detection in ground mobile platforms. To address the under-segmentation of ground points caused by sparse long-range p…

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