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Good day guys,

I am trying to simulate and image with lens barrel distortion. I create a virtual chessboard (only the corners) and then project it onto my image plane using OpenCV. The idea is to project these points with known distortion coefficients, and then attempt a lens distortion calibration (with calibrateCamera), and see if the same coefficients are obtained.

My question is about the projectPoints function which takes distCoeffs as an input. Are these coefficients the same that must be used to undistort an image (output of calibrateCamera)? This means the function will have to calculate the inverse of that operation. Or, does it use those coefficients to distort the object points directly? Meaning that the will not correlate at all at the output of e.g. calibrateCamera.

I ask, because I noticed my simulation does pincushion distortion when I expect barrel, and vica versa. Which seems that the distortion does the opposite of what I think it does.

The minimal working code that I used to simulate the image (in Python):

I am writing a function to search nested js objects for keys or values, returning hits and their paths. At the moment, the path concatenation of the search stages does not work yet. Maybe someone can give me a hint.

Given this test data:

I am trying to use K1 and K2 to correct radial distortion in camera calibration using functions from OpenCV. There are four kinds of combination of sign of K1 and K2:

A K1: positive K2: positive

B K1: positive K2: negative

C K1: negative K2: positive

D K1: negative K2: negative I encounter A， B and C. Is there special meanings for the sign of K1 and K2? There are two kinds of radial distortion: barrel distortion and pincushion distortion. Is the sign of K1 and K2 related to the kind of radial distortion? The more the absolute value of K1 and K2, the larger radial distortion?