在二维图像上查找 3d 透视图

Question

I have an image like this:

I want to find a perpendicular line to the red line (I mean perpendicular line to the track). How can I do this using OpenCV and Python? Problem is that the height of the camera is unknown and a visible angle of 90 degrees is not a real 90 degrees angle. I have found here an option to use OpenCV .projectPoints() method, but looks like it needs to know the position of the resulting point and pass some vector there. Can somebody help how can achieve this? Or is that even possible?

Answer 1

@Chiefir, you don't have enough data to get the perpendicular line you ask for.

I believe your best chance is to find some parallel line in the image, like those marks in the grass (right where the green eleven is).

Some methods look for parallels in the image automatically, assuming a perpendicular straight lines world (like a city of roads and buildings), and get a 3D pose. I don't think those work on you image.

Answer 2

There is very little information in this one image (almost none, in fact) to accomplish your goal, so every solution will necessarily be imprecise. If this is a frame of a video sequence, you can apply the method below to a sequence of frames around this one to improve its accuracy.

One way is to assume that

1. The height of the rail from the ground is small (compared to their distance from the camera).
2. The long edges of the "11" number cut in the grass are perpendicular to the red line.

You can then estimate the vanishing point V of the "11". Then, any line drawn from V to a point of your red line is, by construction, the image of a line on the ground plane orthogonal to the one represented by the red line.

You can improve a little the accuracy by using, instead of your (presumably) hand-drawn red line, a line joining the bottom points of the supports of the rails, since this would be really on the ground.

If the poles supporting the railing were vertical (they aren't, as evidenced by the ones supported by the other rail higher in the image), you could compute their vanishing point P, then use in place of V in the method above.