问题描述
从我对点云如何工作的某种有限的理解中，我认为一个人应该能够从物体外部周围的一组2d图像中生成一个点云.我遇到的问题是，我似乎找不到如何生成这种点云的任何示例.
From my, somewhat limited, understanding of how point clouds work I feel that one should be able to generate a point cloud from a set of 2d images from around the outside of an object. The problem that I am experiencing is that I can not seem to find any examples of how to generate such a point cloud.
推荐答案
通常，从2D图像序列中进行3D形状的重建是一个难题.根据已知的有关相机及其与物体和场景之间关系的信息量，它的范围可以从困难到非常困难.那里有很多信息:尝试对"3D重建图像序列"或"3D图像重建转盘"进行谷歌搜索. 此处是一篇论文，对过程及其挑战进行了很好的总结. 本文是很好的(并且引入了"RANSAC"-另一个很好的搜索关键字). 此链接从面部重构的角度来阐述问题，但理论上可以应用于这个问题.
In general, 3D shaped reconstruction from a sequence of 2D images is a hard problem. It can range from difficult to extremely difficult, depending on the amount of information that is known about the camera and it's relationship to the object and scene. There is a lot of information out there: try googling for "3D reconstruction image sequence" or "3D image reconstruction turn table". Here is one paper that gives a pretty good summary of the process and its challenges. This paper is good (and it introduces "RANSAC" - another good search keyword). This link frames the problem in terms of facial reconstruction, but the theory can be applied to this question.
请注意，对3D点的解释取决于相机的外部和参数.外在参数指定摄像机相对于世界的位置和方向.内部参数将像素坐标映射到世界框架中的坐标.
Note that the interpretation of the 3D points is dependent upon knowledge of the camera's extrinsic and intrinsic parameters. Extrinsic parameters specify the location and orientation of the camera with respect to the world. Intrinsic parameters map pixel coordinates to coordinates in the world frame.
当外部参数和固有参数都不知道时，3D重建对于未知的比例因子是准确的(即，可以建立相对大小/距离，但是绝对大小/距离未知).当两组相机参数均已知时，3D点的比例，方向和位置即为已知. OpenCV文档很好地涵盖了相机校准的概念. 此链接，和也很好.
When neither the extrinsic nor intrinsic parameters are known, the 3D reconstruction is accurate to an unknown scale factor (i.e. relative size/distance can be established, but absolute size/distance is not known). When both sets of camera parameters are known, the scale, orientation, and location of the 3D points are known. The OpenCV documentation covers the concept of camera calibration well. This link, this link, and this link are good, too.
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