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摘要: 首先回顾了摄影测量的历史，从透视几何、成像设备、摄影平台、测量法和测量工具等4个方面较系统地总结了前人的贡献。其次，简要介绍了计算机视觉的起源，并从几何角度分析了计算机视觉与摄影测量之间的紧密联系，探讨了两者在实用上的一些区别。再次，从语义方面，分析了遥感学科的发展，与机器学习和计算机视觉之间的关系，以及目前深度学习和连接主义的盛行。最后，展望了摄影测量的未来，指出与计算机视觉、人工智能等学科的进一步交叉融合是摄影测量发展的必然之路。Abstract: We outline the history of photogrammetry from the aspects of, perspective geometry, camera, platform, measure methods and measure instruments, and summarize previous contributions to photogrammetry. A brief review of computer vision history is given. The tight connections between computer vision and photogrammetry are discussed in terms of geometric principles, and some differences in applications are also considered. From the aspect of semantics, we analyze the development of remote sensing and its relations to machine learning and computer vision, including their common approaches and different applications. The prevailing deep learning raised from connectionism is also reviewed and its successful applications in photogrammetry are analyzed. At last, we expect that the future development of photogrammetry will be more tightly cross-integrated with computer vision, machine learning and artificial intelligence.
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Keywords:
- photogrammetry /
- computer vision /
- remote sensing /
- machine learning
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图 1 多样化的摄影平台(上排：手持仪器架、地面移动测图系统、无人机；下排：无人飞艇、国产运12航摄飞机、测绘卫星；中排：嫦娥月球探测车)
Figure 1. Multiple Photogrammetry Platform (up: Handheld Device, Mobile Measurement System and Drone; Below: Unmanned Airship, Domestic Yun-12 Plane for Aerial Photogrammetry and Mapping Satellite; Middle: Change Lunar Rover)
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图 2 立体坐标量测仪、模拟测图仪和解析测图仪
Figure 2. Stereocomparator, Analog Plotter and Analytical Plotter
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