Artificial intelligence 在搜索算法中使用极线查找两幅相机图像中的对应点

在计算机视觉中，特别是在计算立体中，我们可以很容易地编写一个算法，在两幅相机图像中找到对应的点。该算法可以用如下伪代码编写：

Repeat for each feature point in the left image {
   calculate the epipolar line in the right image 
   if the epipolar line intersects only one feature point 
   then match those points and remove them from the lists
}
Until no feature point can be matched uniquely

我的问题是，如果使用三个摄像头而不是标准的两个摄像头设置，该算法如何改变

仅仅是一些好的想法或者这个伪代码的一些修改版本就太棒了

---

谢谢。

一旦在两幅图像之间有了一对匹配的特征点，您就可以确定剩余图像中这些极线的交点，并以这种方式确定最后一个特征。 因此，您可以为“第一个和第三个”以及“第二个和第三个”相机对重复伪代码：

Repeat for each feature point in the first image {
   calculate the epipolar line in the second image 
   calculate the epipolar line in the third image
   if the epipolar line in either image intersects only one feature point {
     calculate epipolar line for matching feature point in the other image. 
     Intersection with epipolar line from first image gives the third point.
     remove triplet from the list
}
Until no feature point can be matched uniquely.

然后

Repeat for each feature point in the second image {
   calculate the epipolar line in the third image
   if the epipolar line intersects only one feature point {
     calculate epipolar line for matching feature point in the first image. 
     Intersection with epipolar line from second image gives the third point.
     remove triplet from the list
}
Until no feature point can be matched uniquely starting from the second image.