I am trying to calibrate a camera using a checkerboard by the well known Zhang's method followed by bundle adjustment, which is available in both Matlab and OpenCV. There are a lot of empirical guidelines but from my personal experience the accuracy is pretty random. It could sometimes be really good but also sometimes really bad. The result actually varies quite a bit with different sets of the checkerboard placements. Hope someone can explain it from a mathematical stand point so I can consistently get good result.
Does the number of squares in the checkerboard affect the accuracy? Zhang uses 8x8 in his original paper without really explaining why.
Does the length of the square affect the accuracy? Zhang uses 17cm x 17cm without really explaining why.
What is the optimal number of snap shots of different checkerboard position/orientation? Zhang uses 5 images only. I saw people suggesting 20~30 images with checkerboards at various angles, fills the entire field of view, tilted to the left, right, top and bottom. There should be no checkerboard placed at similar position/orientation otherwise the result will be biased towards that position/orientation.
The lens of the camera experimented is a normal rectilinear with 110 degree horizontal FOV.