测绘学报 ›› 2022, Vol. 51 ›› Issue (7): 1437-1457.doi: 10.11947/j.AGCS.2022.20220130

• 摄影测量学与遥感 • 上一篇    下一篇

数字航空摄影三维重建理论与技术发展综述

张力1, 刘玉轩1, 孙洋杰2, 蓝朝桢3, 艾海滨1, 樊仲藜1   

  1. 1. 中国测绘科学研究院摄影测量与遥感所, 北京 100036;
    2. 香港理工大学土地测量及地理资讯学系, 香港 999077;
    3. 信息工程大学地理空间信息学院, 河南 郑州 450047
  • 收稿日期:2022-02-24 修回日期:2022-05-27 发布日期:2022-08-13
  • 通讯作者: 刘玉轩 E-mail:yxliu@casm.ac.cn
  • 作者简介:张力(1970-),男,研究员,主要从事摄影测量、计算机视觉、遥感数据处理相关研究。E-mail:zhangl@casm.ac.cn
  • 基金资助:
    实景三维中国建设专项(121136000000210004)

A review of developments in the theory and technology of three-dimensional reconstruction in digital aerial photogrammetry

ZHANG Li1, LIU Yuxuan1, SUN Yangjie2, LAN Chaozhen3, AI Haibin1, FAN Zhongli1   

  1. 1. Institute of Photogrammetry and Remote Sensing, Chinese Academy of Surveying and Mapping, Beijing 100036, China;
    2. Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong 999077, China;
    3. Institute of Geospatial Information, Information Engineering University, Zhengzhou 450047, China
  • Received:2022-02-24 Revised:2022-05-27 Published:2022-08-13
  • Supported by:
    Special Project for Construction of 3D Real China (No. 121136000000210004)

摘要: 航空摄影测量作为摄影测量学最重要的分支之一,近年来得到了长足的发展。倾斜航空摄影和无人机摄影测量等多种新作业模式的出现,给传统航空摄影测量带来新的挑战的同时也催生出了诸多新的解决方案。此外,人工智能领域计算机视觉技术和深度学习技术中的新理论、新方法不断融入航空摄影测量中,推动航空摄影测量向智能化、自动化方向发展。当代航空摄影测量学已经是多种传感器融合、多种数据采集方式结合、传统摄影测量和人工智能技术交叉的产物。三维重建是航空摄影测量的核心问题之一。本文阐述了当代航空摄影三维重建技术的发展趋势和存在的问题,着重从航空影像的同名连接点自动提取与匹配、区域网平差、密集匹配和单体化建模4个方面对当前的研究现状进行了总结讨论,给出了当前国内外主流的航空影像摄影测量处理框架。

关键词: 当代航空摄影测量, 同名连接点提取, 区域网平差, 影像密集匹配, 单体化建模

Abstract: As one of the essential branches of photogrammetry, aerial photogrammetry has made significant progresses in the past decades. The emergence of various new working modes,such as oblique aerial photography and UAV photogrammetry, has brought new challenges to traditional aerial photogrammetry and has spawned many new solutions. In addition, new theories and techniques in computer vision technology and deep learning technology in artificial intelligence are continuously integrated into aerial photogrammetry, promoting the development of aerial photogrammetry in the direction of intelligence and automation. Therefore, modern aerial photogrammetry is already the product of the fusion of multiple sensors, the combination of various data acquisition methods, and the intersection of computer vision and machine learning technologies in traditional photogrammetry and artificial intelligence technologies. Three-dimensional reconstruction is the core problem of aerial photogrammetry. This paper expounds on the problems existing in modern aerial photogrammetry, summarizes and discusses the current research status from four aspects:corresponding tie points extraction of aerial images; block adjustment; image dense matching; and singleton modeling. And finally this paper gives the mainstream aerial image photogrammetry processing framework at home and abroad.

Key words: modern aerial photogrammetry, corresponding tie points extraction, block adjustment, image dense matching, singleton modeling

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