Giancola's profile - activity

Hi, a have a big question, if square size is dimensionless ( i found a lot of document who confirmed that) why, if i put SS= 10000 or SS=1 i have totally different results in terms of intrinsic parameters?? I thought that should change only exstrinsic's one, but i have different Fx and Fy and in particolar way i have Cx and Cy very very close to ideal central point. Can yoy explain me that?

I tested that the correct value of square size is the half of distance between the circles in asymmetric circle grid while in symmetric circle grid is the distance.

A question, can i compare thees values with the original focal lenght of my camera? My camera has a focal lenght =60mm , and after the calibration in open cv i have fx=38246.8 fy 38074.0 the pixel size is 0,00571

I confirm that the correct order of distorsion coefficents is : [k1, k2, p1, p2, k3, k4, k5 , k6] I have an question about principal point, can we compare it with ideal centrl point fixed in the center of the image? Can we evaluate the goodness of calibration doing this comparison? ( if is it nearer is better? )

Hi, I'm working about a project for my thesis. I have to calibrate my camera to import intrinsic parameters in photoscan fo reconstructon 3D of the object which measures maximum 0,7 x 0,7 mm. I calibrate the camera with openCv, photographing a symmetric pattern glass with circle grid (0,5 is the diameter of each circle) or an asymmetric circles grid (13x4 circles diameter=1mm). I do 24 photos, 8 for each kind of inclination ( horizontal vertical and oblique)

1)I would know how can I evaluate the calibration? I know that Reprojection Errors isn't an absolute evaluation, can I compare cx and cy with the real center of the image? Can I evaluate the values of distorsion parameters?(How?)

2) Is better fixing the principal point? or fixing something else?

Any other suggestion is welcome

I have this questions too :( . But i do a lot of experiments. I found a linear trend between the resolution and Repr.Err. Like you if i reduce the resolution, i have a smaller Repr.Err. I use a Canon EOS400 which full resolution is 3888x2592, i take 20-25 shoots changing inclinations of pattern ( i use a micro pattern 20x20mm more or less, symmetric and printed on glass, so the circles are perfect), with this settings i have a Repr.Err around 0,24. If i reduce the resolution to 972x648(4 times smaller) the error drops to 1/4 , approximately to 0,06, and if i reduce to 1944x1296( two times smaller) i have a Repr.Err = 0,12. I repeat this for a lot of set , i think that there is a correspondence . Maybe the explanation could be in the image with full resolution we have in the same space more pixel so the error is bigger, but i don't find any official document who explains this better.

There is a book, a document who explain this? i need it to write in my thesis :)

Hi i'm using openCv and cameraCalibration to work about my thesis. I use a Canon EOS400, the size of image is 3888x2592 ( full resolution)but i have an asymmetric circles grid printed on paper so it isn't very accurate ( i use tha maximum zoom for my aim) and OpenCv doesn't ricognize the circles so it doesn't work. For this reason i have to reduce the size of image with Photoshop to obtained photo which size is 972x648(4 times smaller). Does this reduction influence Reprojection Error? It will be 4 times smaller? Is there a paper, a document, something which prove this? Finally can i express Repr.Error dividing the value with N°total of pixel to compare the results of different size of images?