A Survey of Multi View Stereo

Fengxiang Rong, Dongfang Xie, Wei Zhu, Huiliang Shang, Liang Song
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引用次数: 1

Abstract

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.
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多视点立体技术综述
三维重建是通过传感器获取真实物体的轮廓、颜色、深度等信息,然后将现实世界中的三维物体转化为可被计算机处理和显示的三维模型的过程。根据传感器的不同,获取数据的方式也多种多样,其中基于视觉的三维重建技术因其应用范围更广、发展前景更大,一直是该领域的研究热点。目前已经发展了单眼、立体等重建方法,MVS (Multi View Stereo)也在这个过程中自然发展起来。本文将从传感器类型入手,总结三维重建方法的发展历程,重点介绍多视角立体方法,包括SFM (Structure from Motion)中的特征点匹配和SFM重建方法、传统MVS方法的实现和深度学习方法的实现。最后对该领域的总体发展进行了总结,并对未来的发展进行了展望。
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