密集像素逆投影
我看到一个关于反向投影 4 个 2D 点以得出 3D 空间中矩形的角的问题。 我对同一问题有一种更通用的版本：
给定焦距（可以解决以产生弧秒/像素）或内在相机矩阵（定义所使用的针孔相机模型的属性的 3x2 矩阵 -它与焦距直接相关），计算穿过每个像素的相机光线。
我想拍摄一系列帧，从每个帧中导出候选光线，并使用某种迭代求解方法从每个帧中导出相机姿势（当然，给定足够大的样本）...全部其中实际上只是广义霍夫算法的大规模并行实现......它首先获得了我遇到问题的候选射线......
I saw a question on reverse projecting 4 2D points to derive the corners of a rectangle in 3D space. I have a kind of more general version of the same problem:
Given either a focal length (which can be solved to produce arcseconds / pixel) or the intrinsic camera matrix (a 3x2 matrix that defines the properties of the pinhole camera model being used - it's directly related to focal length), compute the camera ray that goes through each pixel.
I'd like to take a series of frames, derive the candidate light rays from each frame, and use some sort of iterative solving approach to derive the camera pose from each frame (given a sufficiently large sample, of course)... All of that is really just massively-parallel implementations of a generalized Hough algorithm... it's getting the candidate rays in the first place that I'm having the problem with...
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我的一个朋友从一所大学找到了 PhotoSynth 中相机匹配的源代码。 如果我是你，我会用谷歌搜索一下。
A friend of mine found the source code from a university for the camera matching in PhotoSynth. I'd Google around for it, if I were you.
经过一番探索后，难道不是外在矩阵告诉你相机在 3 空间中的实际位置吗？
我在一家做了很多这样的事情的公司工作，但我总是使用算法人员编写的工具。 :)
After a little poking around, isn't it the extrinsic matrix that tells you where the camera actually is in 3-space?
I worked at a company that did a lot of this, but I always used the tools that the algorithm guys wrote. :)
这是一个很好的建议......我肯定会研究它（photosynth 有点重新激发了我对这个主题的兴趣 - 但我已经为 robochamps 工作了几个月） - 但它是一个稀疏的实现 - 它寻找“好的” “特征（图像中的点应该在同一图像的其他视图中很容易识别），虽然我当然计划根据特征的匹配程度对每个匹配进行评分，但我希望使用完整的密集算法来导出每个像素...或者我应该说体素哈哈？
That's a good suggestion... and I will definitely look into it (photosynth kind of resparked my interest in this subject - but I've been working on it for months for robochamps) - but it's a sparse implementation - it looks for "good" features (points in the image that should be easily identifiable in other views of the same image), and while I certainly plan to score each match based on how good the feature it's matching is, I want the full dense algorithm to derive every pixel... or should I say voxel lol?