从轴对齐照片进行 3D 重建
在浏览了有关该主题的其他主题后，我相信我的问题可能有一个相当简单的答案。我得到了一个对象的六张轴对齐照片的集合，例如：
http://www.flickr.com/photos/nnenn/4479290754/in/photostream
是否有任何算法可以重建此图像的 3D 近似值 目的？我尝试并取得了一定成功的一件事是创建六个 3 维“棱镜”（每张图片一个），它们在 x、y 或 z 方向上是无限的，并取它们的交集。这工作正常，但它对输入有点敏感，我想知道是否有更强大的众所周知的东西。我应该补充一点，我预计显然需要一些手动干预，但我想知道如何最大限度地减少此类必要干预的数量。
一个可能有用的子例程如下所示：假设我要获取六张照片中的每个像素并将其识别为一个组件，因此例如属于驾驶舱的所有像素都标记为“1”，所有属于最左边的像素导弹被标记为“2”，依此类推。这对重建有帮助吗？
谢谢！
Having poked through the other threads on this topic, I believe there may be a reasonably simple answer to my question. I'm given a collection of six axis-aligned photographs of an object, such as this:
http://www.flickr.com/photos/nnenn/4479290754/in/photostream
Are there any algorithms that would reconstruct a 3d approximation of this object? One thing that I tried with marginal success was to create six 3-dimensional "prisms" (one for each picture) that are infinite in the x-, y-, or z-direction, and take the intersection of these. This works OK, but it's a bit sensitive to the inputs and I'd like to know if there's something more robust that's well-known. I should add that I expect that some manual intervention is clearly going to be required, but I'd like to know how to minimize the amount of such intervention necessary.
One subroutine that might be useful is something like the following: suppose I were to take each pixel in the six photos and identify it to a component, so e.g. all pixels belonging to the cockpit were labelled "1", all pixels belonging to the leftmost missile were labelled "2", and so forth. Would this help in the reconstruction?
Thanks!
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这几乎是“空间雕刻”或体积相交解决方案的教科书示例。 这里是对该论文的合理介绍。
This is almost a textbook example for a "space carving" or volume intersection solution. Here is a reasonable introduction to the paper.