多相机图像拼接 [英] Multiple camera image stitching

问题描述

我一直在运行一个从多台摄像机拼接图像的项目，但是我认为我遇到了瓶颈...对此问题我有一些疑问.

I've been running a project of stitching images from multiple cameras, but I think I've got a bottleneck...I have some questions about this issue.

我想将来将它们安装在车辆上，这意味着摄像机的相对位置和方向是固定的.

I wanna try to mount them on a vehicle in the future and that means the relative positions and orientations of cameras are FIXED.

另外，由于我使用的是多台摄像机，并尝试使用HOMOGRAPHY拼接它们中的图像，因此我将摄像机尽可能地靠近，以免出现错误(由于摄像机的焦点不在相同的位置，这是不可能的，因为相机占据了一定的空间.)

Also, as I'm using multiple cameras and try to stitch images from them using HOMOGRAPHY, I'll put cameras as close as possible so that the errors(due to the fact that the foci of the cameras are not at the same position and it's impossible as cameras occupy certain space.) can be reduced.

这是我的简短实验视频. http://www.youtube.com/watch?v=JEQJZQq3RTY

Here's a short experiment video of mine. http://www.youtube.com/watch?v=JEQJZQq3RTY

如图所示，拼接结果非常糟糕... 即使摄像机捕获的场景是静态的，但单应性仍然保持变化.

The stitching result is very terrible as shown there... Even though the the scene captured by the cameras is static, the homography still keeps varying.

以下链接是我到目前为止所做的代码，code1.png和code2.png是图片，显示了我在Stitching_refind.cpp中的代码的一部分.

The following link is the code I've done so far and code1.png and code2.png are pictures that show part of my code in Stitching_refind.cpp.

https://docs.google.com/folder/d /0B2r9FmkcbNwAbHdtVEVkSW1SQW8/edit?pli = 1

几天前，我已经更改了代码中的某些内容，例如执行步骤2、3和4(请检查上面提到的2张png图片).

I've changed some contents in the code a few days ago such as to do the Step 2, 3 and 4(Please check the 2 png pictures mentioned above) JUST ONCE.

总而言之，我的问题是:

To sum up, my questions are:

1.在计算特征之前是否可以找出重叠区域? 我不想在整个图像上计算特征，因为这将导致更多的计算时间和不匹配. 我想知道是否可以仅在两张相邻图像的重叠区域中使用计算机功能?

1. Is it possible to find out overlapping regions before computing features? I don't want to compute the features on the whole images as it will result in more computational time and mismatches. I wonder if it's possible to JUST computer features in the overlapping region of 2 adjacent images?

2.如何使获得的单应性更加精确? 有人说过相机校准"，然后尝试其他匹配方法. 我还是Computer Vision的新手... 我尝试研究一些有关相机校准的材料，但我仍然不知道它的用途.

2.What I can do to make the obtained homography more accurate? Some people spoke of CAMERA CALIBRATION and try some other matching method. I'm still new to Computer Vision... I tried to study some materials about Camera calibration but I still have no idea what it is for.

大约2个月前，我在这里问了类似的问题: 在使用OpenCV进行图像拼接时遇到一些困难

About 2 months ago I asked a similar question here: Having some difficulty in image stitching using OpenCV

，其中一位回答者克里斯说:

,where one of the answerer Chris said:

听起来您正在明智地进行此操作，但是如果您有 访问两个摄像头，它们将保持静止不动 互相尊重，然后离线进行校准，然后简单地应用 在线转换将使您的应用程序更高效.

It sounds like you are going about this sensibly, but if you have access to both of the cameras, and they will remain stationary with respect to each other, then calibrating offline, and simply applying the transformation online will make your application more efficient.

离线校准"是什么意思?它有什么帮助?

What does "calibrate offline" mean? and what does it help?

感谢您的任何建议和帮助.

Thanks for any advice and help.

推荐答案

如Chris所写:

However, your points are not restricted to a specific plane as they are 
imaging a 3D scene. If you wanted to calibrate offline, you could image 
a chessboard with both cameras, and the detected corners could be used
in this function.

离线校准意味着您使用了一些易于检测的校准模式.然后计算转换矩阵.进行此校准后，您可以将此(先前计算的)矩阵应用于采集的图像，它应该可以为您工作.

Calibrate offline means that you use some callibration pattern easy to detect. Then compute transformation matrix. After this calibration you apply this (previously computed) matrix to acquired images ,it should work for you.

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