2D图像的三维重建 [英] 3D reconstruction from 2D images

问题描述

我正在开发一个关于Android中2D图像3D重建的项目。那些2D图像是超声黑白图像。是否有任何工具包或开发人员可以帮助我？

I am working on a project about 3D reconstruction from 2D images in Android. Those 2D images are ultrasound black and white images. Is there any toolkit or developer sources could help me??

推荐答案

Wikepedia可能是一个起点： 3D数据采集和对象重建 - 从2D图像采集 [ ^ ]。

Wikepedia could be a starting point: 3D data acquisition and object reconstruction - Acquisition from 2D images[^].

请看这里： http ：//en.wikipedia.org/wiki/Ambiguous_image [ ^ ]。



也许，对你来说这些想法都是微不足道的，但这个页面清楚地说明了：这个问题在解决方案一词的评论意义上无法解决。这就是所谓的不适定问题。



请阅读不适定问题的概念 。经典的Tikhonov关于不适定问题的理论引入了广泛类别的良好问题的标准。对于不适定问题，引入了准解决方案的概念。你正在处理的问题属于那些不适定问题的类别。您可能理解，严格来说，每组二维图像都允许无限多个解决方案。软件应该寻找最可能或最简单的软件，这也很难定义，并且无法在所有情况下定义。



请参阅：

http://en.wikipedia.org/wiki/Well-posed_problem [ ^ ]，

http://en.wikipedia.org/wiki/Tikhonov_regularization [ ^ ]。



我只想解释这个问题非常困难;所以无论你使用什么，都不应该期待太好的结果。有很多情况（其中一些是人工设计的），即使是人类也会犯错误。

-SA

Please look here: http://en.wikipedia.org/wiki/Ambiguous_image[^].

Perhaps, for you these ideas are trivial, but this page clearly illustrates: the problem is not resolvable in the comment sense of the word "solution". This is so-called ill-posed problem.

Please read on the concept of ill-posed problem. The classical Tikhonov's theory of ill-posed problems introduces the criteria for a well-posed problem of a wide class. For ill-posed problems, the concept of quasi-solution is introduced. The problem you are dealing with belongs to the class of those ill-posed problems. You probably understand that each set of 2-dimensional image, strictly speaking, allows for infinite number of solutions. The software should seek for "most likely" or "simplest" one, which is also hard to defined and cannot be defined in all cases.

Please see:
http://en.wikipedia.org/wiki/Well-posed_problem[^],
http://en.wikipedia.org/wiki/Tikhonov_regularization[^].

I just mean to explain that the problem is extremely difficult; so you should not expect too good results, no matter what you use. There are many cases (some of them are artificially designed), when even a human being makes mistakes.

—SA

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