Question

我正在建立一个网站,利用计算机视野技术冷却物品,用户使用自己的网络机对视频进行现场记录和上载。为此,我需要照相机的内在和扭曲参数。鉴于用户上载的录像,我正试图指出,这是计算这些录像的最佳方法。我们不能假设录像用户可能装载什么,但合理的假设是,一个人可能出现在录像中。我仍在这样做的初期阶段,但我很想知道其他人如何解决这一问题。

具体地说,下面是我对小组中有经验的人可能评论的问题:

What algorithms, libraries and techniques are available to extract intrinsic and distortion parameters of any generic webcam available in the market? [I say "extract" and not "calibrate" to include cases where intrinsic parameters are just a method call away with no calibration necessary].
In general, how much variance have you observed in the intrinsic and distortion parameters in the webcams available in the market? Did you approximate them with a single intrinsic and distortion parameters or what approach did you follow?
What camera self-calibration methods, if any, could be employed in these scenarios? Are there any opensource or commercial libraries available which might be of some help?
If we aim to calibrate the webcams using the videos user record and upload, what assumptions in the parameters [like fx==fy or no distortion params] makes sense and sounds reasonable to you?
Would a reasonable approximation of intrinsic and distortion params for all the cameras make sense? What would be a reasonable approach to validate how good particular intrinsic and distortion parameters are for a specific webcam?
Are there any other issues that need to be considered?

Answer 1

有时,我听到坏消息: 我现在就是这样。

几乎你们的所有观点都明确答案是,没有,没有,也没有。仅就最后一点而言,就其他问题而言,答案不是没有的,而是很长的清单:

实际上,没有套头和一些具体制约因素的摄像校准几乎是不可能的。

最近在开放式消费物价指数的 st化模块中找到了最接近于放弃的校准。 Hovewer说,它并非完美无缺,它不使用随机录像。把它当作审判。

Answer 2

http://www.vision.caltech.edu/bouguetj/calib_doc/“rel=“nofollow” 摄像机调节工具箱,良好的Matlab执行,提取内在参数和外在参数。
不仅网络运动之间存在差异,而且:
- Different modules
- Different zoom levels (Affects the optics)
我认为,如果你限制休庭,对录像不作假设,这是一个真正的难题。如果你不使用已知的东西,例如照相机校正工具箱中的检查板,那么校准和评价就很难。

Answer 3

Many algorithms, including the currently used in opencv requires that known points can be detected (e.g corners in a chess board). You would have to require that your users took pictures of this known patterns, which ruin the concept of random videos. I dont have a solution to this but you might want to consider requiring users to record videos of structures scenes(no specific patterns or objects) and use the algorithm described in: "Camera calibration with lens distortion from low-rank textures" http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5995548&tag=1

曾尝试过。

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