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.