计算对应像素
我有一个带有两个摄像头的计算机视觉。其中一台相机是飞行时间相机。它为我提供了场景中每个像素的深度。另一台相机是标准相机，可以为我提供场景的彩色图像。
我们想使用深度信息从彩色图像中删除一些区域。我们计划在彩色图像中跟踪物体、人和手，并希望借助飞行时间相机去除远处的背景像素。目前还不确定相机是否可以平行设置。
我们可以使用 OpenCv 或 Matlab 进行计算。
我读了很多关于整流、对极几何等的内容，但我仍然无法看到计算每个像素的对应关系所必须采取的步骤。
您会使用什么方法，可以使用哪些功能。您会将问题划分为哪些步骤？有可用的教程或示例代码吗？
更新我们计划使用场景中放置的已知标记进行自动校准
I have a computer vision set up with two cameras. One of this cameras is a time of flight camera. It gives me the depth of the scene at every pixel. The other camera is standard camera giving me a colour image of the scene.
We would like to use the depth information to remove some areas from the colour image. We plan on object, person and hand tracking in the colour image and want to remove far away background pixel with the help of the time of flight camera. It is not sure yet if the cameras can be aligned in a parallel set up.
We could use OpenCv or Matlab for the calculations.
I read a lot about rectification, Epipolargeometry etc but I still have problems to see the steps I have to take to calculate the correspondence for every pixel.
What approach would you use, which functions can be used. In which steps would you divide the problem? Is there a tutorial or sample code available somewhere?
Update We plan on doing an automatic calibration using known markers placed in the scene
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如果您想要可靠的对应关系，您应该考虑 SIFT。 MATLAB 中有多种实现 - 我使用 Vedaldi-Fulkerson VL Feat 库。
如果您确实需要快速性能（我认为您不需要），您应该考虑使用OpenCV< /a> 的 SURF 检测器。
如果您还有其他问题，请询问。 这个其他答案<我的 /a> 可能有用。
PS：通过对应关系，我假设您想要找到两个图像上同一 3D 点的投影坐标 - 即坐标
(i,j)图像 A 中的像素u_A和图像 B 中的u_B的像素，这是同一点在 3D 中的投影。If you want robust correspondences, you should consider SIFT. There are several implementations in MATLAB - I use the Vedaldi-Fulkerson VL Feat library.
If you really need fast performance (and I think you don't), you should think about using OpenCV's SURF detector.
If you have any other questions, do ask. This other answer of mine might be useful.
PS: By correspondences, I'm assuming you want to find the coordinates of a projection of the same 3D point on both your images - i.e. the coordinates
(i,j)of a pixelu_Ain Image A andu_Bin Image B which is a projection of the same point in 3D.