在搜索算法中使用极线来查找两个相机图像中的对应点

发布于 2024-11-05 02:17:35 字数 455 浏览 8 评论 0原文

在计算机视觉中,特别是在计算立体中,我们可以轻松编写算法来查找两个相机图像中的对应点。该算法可以用伪代码编写,如下所示:

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,如何更改该算法?

只要有一些好的想法或者这个伪代码的一些修改版本就很棒了。

谢谢。

In computer vision, specifically computational stereo, we can easily write an algorithm to find corresponding points in the two camera images. The algorithm can be written in pseudo-code like this:

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

My question is how can this algorithm be changed if three cameras are used instead of the standard two camera setup?

Just some good ideas or some altered version of this pseudo code would be brilliant.

Thank you.

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他是夢罘是命 2024-11-12 02:17:37

一旦在任一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,并以此方式确定最后一个特征。
因此,您可以为“第一和第三”和“第二和第三”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.

Once you have a matching pair of feature points between either of the images you can determine the intersection of these epipolar lines in the remaining image and determine the last feature that way.
So you can repeat your pseudocode for the "first and third" and "second and third" camera pair:

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.

then

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.
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