【读论文】点云智能研究进展与趋势（2019）

【读论文】点云智能研究进展与趋势（2019）
杨必胜
doi: 10.11947/j.AGCS.2019.20190465

摘要：关键词：点云大数据采集装备点云场景：从可视化量测到智能化场景展望：

随着以激光扫描、倾斜摄影为主的各种现实采集（reality capture）装备的快速发展，点云已成为继矢量地图和影像数据之后的第三类重要的时空数据源，并在地球科学、空间认知、智慧城市等科学研究和工程建设中发挥越来越重要的作用。如何从点云大数据中快速、准确获取精准有效的三维地理信息成为测绘地理信息领域的科学前沿和地学应用研究的迫切需求，也是三维地理信息获取与建模面临的重大难题。点云智能应运而生，并成为突破上述难题的科学途径。本文围绕点云智能中的三个重要方向：点云大数据处理的理论方法，点云大数据智能处理关键技术和重大工程应用，阐述点云采集装备、智能化处理，以及科学研究与工程应用的最新进展，最后对点云智能的重要发展方向趋势予以展望，希望为点云研究相关人员提供科学参考。

点云大数据；点云智能；语义标识；结构化建模；深度学习；广义点云

①发展点云大数据的储存与更新机制，为点云的高效、深度利用提供基础支撑；

②建立面向新型基础测绘的点云三维信息提取与建模的行业和国家标准，服务实景三维中国建设和自然资源监测；

③发展面向地球大数据的点云精准理解、综合人工智能、深度学习等，建立点云大数据对象化深度学习网络，在全球、区域、单体对象上对场景精准理解；

④研制采集、处理与服务一体化的智能装备，服务重大基础设施（如：电网、高铁、交通等）健康管理。

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