A Survey of Multi View Stereo

3D reconstruction is the process of obtaining the contour, color, depth, and other information of the real object through the sensor, and then transforming the 3D object in the real world into a 3D model that can be processed and displayed by the computer. According to the different sensors, there are a variety of ways to obtain data, among which the vision-based 3D reconstruction technology has been the focus of research in this field because of its wider scope of application and greater development prospects. At present, monocular, stereoscopic, and other reconstruction methods have been developed, and MVS (Multi View Stereo) is naturally developed in this process. This paper will start from sensor types, summarize the development process of 3d reconstruction methods, and focus on the introduction of multi-perspective stereo methods, including feature point matching in SFM (Structure from Motion) and SFM reconstruction method, traditional MVS method implementation and deep learning method implementation. Finally, the overall development of this field is summarized, and the future development is prospected.