New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Calibration from vanishing points #6
Comments
Not sure if I understand correctly, could you list your S matrix here? The condition number should be only related to the relative scale. |
Sorry for the confusion. My goal is to estimate the focal length f of the camera, which will involve solving for the matrix S, especially its first element which is equal to 1/f^2 (in order to find f). My concern is that this number can very small. For example, if the ground truth f is 1000, then 1/f^2 = 1e-6. This number is very small and with small numerical error, the estimated focal length f will be way off from the ground truth f. Hope it clarifies things. |
Since the 1/f^2 is before the whole matrix, it should not matter. Please post the value of your matrix S and its condition number so I can better understand your problem. |
Anyway, I guess your problem is ox^2 + oy^2 + f^2 is too large. You may want to rescale the unit so that they are around 1. |
If you still have issues, feel free to reopen this post. |
Hello,
Thanks for your great work. I have a question about "Calibrating from three orthogonal vanishing points". This is a classic problem and it's not the main point of your paper, but I also read about it in your blog (https://yichaozhou.com/post/20190402vanishingpoint/) and my question is, the first element (S_{11}) of the matrix S = K^-T K^-1 is 1/f^2, which will be very small when f is sufficiently large, leading to numerical instability. Do you have any idea how to handle this? Thanks in advance.
The text was updated successfully, but these errors were encountered: