计算右图像的深度图 [英] Calculate Depth map of right image

问题描述

我做了什么：
要从左图（给定）创建一个新的视图（右图），我使用的公式纯视图之间的翻译（从Zissermann书）为：

x'= x + Kt / Z

x'= [u'
v'
1] ;
x = [u
v
1];
K = [f 0 cx; 0 f cy; 0 0 1];
t = [t1 t2 t3] ^ T;
Z - 左图像中的像素深度

图像和相机矩阵取自Middlebury stereo 2014数据集。

通过实现这个，
我有一个带有漏洞的图片（黑色区域）。

我需要做的： p>

为了填补这些洞，有几种算法在修改之前修改右视图的深度图。

告诉我如何找到我的合成（右）视图的深度图？

results matlab
以上是我到现在为止的结果，请帮助！

解决方案

我的回答实际上是从 Priyamvadha的上一个问题和我的答案的解决方法。
如果您有外在/内在参数和3D点，请考虑反转过程。

1. 转换（如同我前面的答案）所有的3D点在正确的相机参考系> R 和 t ，转换转换）




2. 系统，记住Z值与每个点及其Z坐标的视差




3. 强烈相关，差异应等于

   
   
   

   D =（b * f）/ Z

和f是来自内在函数的焦距。

您应该已经为合成图像获得了合成的差异。将每个视差值与合成图像中的相应投影点相链接。

是的，我可以加入所有段落并给出一个唯一的公式，对你来说意味着什么。

PS如果你没有意义，图片中就不会有黑洞的深度。

What I have done: To create a novel view(right image) from left image(given), I used the formula for pure translation between views(from Zissermann book) as:

x' = x + K.t/Z

x'= [u' v' 1]; x = [u v 1]; K = [f 0 cx; 0 f cy;0 0 1]; t = [t1 t2 t3]^T; Z - depth of pixel in left image

The images and camera matrix were taken from Middlebury stereo 2014 dataset.

By implementing this, I have an image with holes(black regions) due to disocclusions.

What I need to do :

To fill these holes, several algorithms exist which modify the depth map of right view prior to warping.

Can you tell me how I can find depth map of my synthesized(right) view ?

results matlab Above is the result I have got till now, please help!

解决方案

My answer actually is a workaround from Priyamvadha's previous question and my answer to it. If you have extrinsic/intrinsic parameters and 3D points, consider to reverse the process.

1. transform (as you did with my previous answer) all the 3D points in the right camera's reference system (use extrinsic R and t, "reversing" the transformation)

2. now that you have all the 3D coordinates in that system, remember that the Z value is strongly linked with the disparity

3. for each point and its Z coordinate, the disparity should be equal to

   D = (b*f)/Z

with b the baseline and f the focal length from intrinsics.
You should have obtained syntethized disparity for your syntetized image. Link each disparity value with the correspondant projected point in the syntethized image.

Yes, I could have join all the passage and give you a unique formula, but it would not have meant anything for you.

PS if you have no point, there will be no depth for black holes in the image.

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