点云智能研究进展与趋势

doi:10.11947/j.AGCS.2019.20190465

摘要/Abstract

摘要： 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。

关键词: 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

Abstract: With the rapid development of the reality capture, such as laser scanning and oblique photogrammetry, point cloud has become the third important data source following vector maps and imagery, and also plays an increasingly important role in scientific research and engineering in the fields of earth science, spatial cognition, and smart city, and so on. However, how to acquire valid and accurate three-dimensional geospatial information from point clouds has become the scientific frontier and the urgent demand in the field of surveying and mapping as well as the geoscience applications. To address the challenges mentioned above, point cloud intelligence came into being. This paper summarizes the state-of-the art of point cloud intelligence in acquisition equipment, the intelligent processing, scientific research and the major engineering applications, focusing on its three important areas:the theoretical methods, the key techniques of intelligent processing and the major engineering applications. Finally, the promising development tendency of the point cloud intelligence is summarized.

Key words: point cloud big data, point cloud intelligence, semantic labeling, structured modelling, deep learning, ubiquitous point cloud

中图分类号:

P237
TP301

杨必胜, 董震. 点云智能研究进展与趋势[J]. 测绘学报, 2019, 48(12): 1575-1585.

YANG Bisheng, DONG Zhen. Progress and perspective of point cloud intelligence[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(12): 1575-1585.

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