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I ran Bouguet's calibration toolbox (http://www.vision.caltech.edu/bouguetj/calib_doc/htmls/example.html) on Matlab and have the parameters from the calibration (intrinsic [focal lengths and principal point offsets] and extrinsic [rotation and translations of the checkerboard with respect to the camera]).

Feature coordinate points of the checkerboard on my images are also known.

I want to obtain rectified images so that I can make a disparity map (for which I have the code for) from each pair of rectified images.

How can I go about doing this?

David
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2 Answers2

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The documentation is here. At the end, it reads "Add these values as constants to your program, call the initUndistortRectifyMap and the remap function to remove distortion and enjoy distortion free inputs with cheap and low quality cameras".

Once your cameras are rectified, you may be interested in the class StereoVar or StereoBM to get the disparity map. Use reprojectImageTo3D once you are done if you want to check that your results look fine in 3D.

ChronoTrigger
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  • Can you take a look at my code? stereoRectify isn't working for some reason... https://gist.github.com/anonymous/6586653 It might be worthy to note that I did not use stereo cameras. It was just one camera, and images were taken with the camera moving relative to the scene. Is stereoRectify still applicable here? Calibration parameters were found with Bouguet's toolbox. – David Sep 16 '13 at 21:13
  • I don't think you can use the stereoRectify with two general cameras, but I'm not sure. Check if you can use some bundle adjustment or structure from motion technique. – ChronoTrigger Sep 16 '13 at 22:03
  • What do you mean by two 'general' cameras? It was just one camera, and the two images came from that one camera. Shouldn't it be possible to treat the two images that came from the one camera as stereo pair images by having the stereoRectify parameters cameraMatrix1 = cameraMatrix2 and distCoeffs1 = distCoeffs2? Thanks for the help, btw. – David Sep 16 '13 at 23:21
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If fully calibrated use: http://link.springer.com/article/10.1007/s001380050120#page-1 Both cameras have the same orientation, share the same R.

First row of the new R is the baseline = subtraction of both camera centers. Second row cross product of baseline with old left z-axis (3 row R_old_left). Third row cross product of the first two rows.

Warp images with H_left=P_new(1:3,1:3)*P_old_left(1:3,1:3)^-1 and H_right=P_new(1:3,1:3)*P_old_right(1:3,1:3)^-1.

Rectified left pixel coordinates are u_new=(h11*u+h12*v+h13)/(h31*u+h32*v+h33), v=(h21*u+h22*v+h23)/(h31*u+h32*v+h33), same with the right ones

YuZ
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