I am trying to find out intrinsic parameters(focal length ,principle point,and lens distortion coefficients)as well as the extrinsic parameters(rotation and translation of each camera relative to the reference frame) of three cameras in the flowing picture. enter image description here

They are placed at nearly orthogonal angles around a 12x12x12 inch working space. There are four steps:

  1. capture images of chess board by two cameras at the same time
  2. use toolbox calib_gui(matlab) to calibrate two cameras separately and get Calib_Results_left.mat and Calib_Results_right.mat.
  3. put these two results into stereo_calib(matlab) and run Calibration
  4. repeat step 1~3 on another pair of cameras

However, I was stuck at step 3! None of pair images was found inconsistent. The errors were shown in the following form:

Disabling view 2 - Reason: the left and right images are found inconsistent (try help calib_stereo for more information)

I checked the order of images but didn't find problems. I doubt that my application is not binocular calibration, because intersection angle between two cameras is too big for a stereo-camera!

I just want to find out rotation and translation of each camera relative to the reference frame. Does anybody have any ideas?


Use an asymmetric calibration plate. Such as the new circle grid in OpenCV. Check here. You do not need to find the correspondences in the gui, but rather run the calibration directly. Also, do not forget to initialize the optimization problem using the median of the obtained poses.

To calibrate multiple view setups, I would also recommend Multi Camera Self Calibration tool. It uses a simple laser dot and is much easier to calibrate, especially when the number of cameras increase. Of course, pay attention to the synchronization.

  • $\begingroup$ It is so amazing that I could figure out extrinsic parameters without finding the correspondences! Anyway, what do you mean by " initialize the optimization problems...."? I never notice whether there is a problem of optimization? $\endgroup$ – oilpig Dec 23 '14 at 13:51
  • $\begingroup$ Calibration is basically an optimization problem. This is what I meant. $\endgroup$ – Tolga Birdal Dec 23 '14 at 22:36

For pairwise stereo calibration try using the Stereo Camera Calibrator app in the Computer Vision System Toolbox. It is much easier to use than Caltech Camera Calibration toolbox. For starters it detects the checkerboard automatically.

  • $\begingroup$ Stereo calibration toolbox from caltech didn't work well at all. I think it is not a problem of convenience. Should I choose another method to calibrate two cameras at the orthogonal positions? $\endgroup$ – oilpig Dec 24 '14 at 13:43

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.