Strange values for matrix camera and distortion values

asked 2017-07-14 14:24:09 -0500

RdlP gravatar image

updated 2017-07-17 05:56:49 -0500

I am trying to calibrate a fisheye camera. In order to do that I load a video take with that camera and takes frames where appears a cheesboard pattern. In order to find patterns I use:

bool found = findChessboardCorners(image_to_show, board_sz, corners, CALIB_CB_ADAPTIVE_THRESH | CALIB_CB_NORMALIZE_IMAGE | CALIB_CB_FAST_CHECK);
        if(found)
        {
            cornerSubPix(gray_image, Mat(corners), Size(11, 11), Size(-1, -1), TermCriteria(CV_TERMCRIT_EPS | CV_TERMCRIT_ITER, 30, 0.001));
            drawChessboardCorners(gray_image, board_sz, Mat(corners), found);
        }

when I take 15 pattern I calibrate the camera as follow:

double error = fisheye::calibrate(object_points, image_points, image_to_show.size(), intrinsic, distCoeffs, rvecs, tvecs, fisheye::CALIB_RECOMPUTE_EXTRINSIC | fisheye::CALIB_CHECK_COND | fisheye::CALIB_FIX_SKEW);

In this case the error is: 1.6847, then I print the intrinsic matrix and distortion coeficients and I get

Intrinsic Matrix
[251.48312, 0, 471.14383;
 0, 255.30005, 501.81467;
 0, 0, 1]

Distortion coefficients
[0.055155002;
 0.07189583;
 -0.082159713;
 0.026405662]

I think this values are wrong because the image resolution is 2048x2048, si cx and cy should be 1024 but the calibration method returns 471 and 501 for that variables.

then I try

fisheye::undistortImage(image_to_show, imageUndistorted, intrinsic, distCoeffs);

But I get a black image in imageUndistorted

This is the undistorted image that I get after calibration

Result

Image1
Image2 Image3 Image4

Edit: I modify my program to take images instead of video stream and now I am using a flat chessboard pattern.

Image1
Image2 Image3

If I use the fisheye::undistortImage the result is the same (more or less) than before, but if I use

Mat newCamMat;
Mat view, result, map1, map2;
fisheye::estimateNewCameraMatrixForUndistortRectify(intrinsic, distCoeffs, image_to_show.size(), Matx33d::eye(), newCamMat, 1);
fisheye::initUndistortRectifyMap(intrinsic, distCoeffs, Matx33d::eye(), newCamMat, image_to_show.size(), CV_16SC2, map1, map2);
remap(image_to_show, result, map1, map2, INTER_LINEAR);

I get something similar to this

result.

so, seems that fisheye::undistortImage doesn't work well. The result that I have obtanined is closer to solution but It still seems wrong. How can I get a better result?

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Comments

When you look at the images with the detected corner points drawn on, are the detected corners in approximately the right place? And does the chessboard occupy a variety of positions in your images? Could you show some examples of the images you used?

AJW gravatar imageAJW ( 2017-07-15 02:13:08 -0500 )edit

For now i can't show image examples, but I update the question with the calibration result. I can say that the corner in the image are detected in the right place and the chessboard pattern appear in different position and also in different orientations in the input frames.

RdlP gravatar imageRdlP ( 2017-07-15 03:51:55 -0500 )edit

I update the question with some of the pattern detected (I cut the image to show only the chessboard pattern)

RdlP gravatar imageRdlP ( 2017-07-16 17:56:35 -0500 )edit
1

your images look terrible. the board is not plain (laminate it onto something), sometimes corners are not visible, fingers get in the way.

also, rather do this with a list of images, not a video stream, because it's much easier to replace bad images with new , better ones then.

berak gravatar imageberak ( 2017-07-17 02:02:08 -0500 )edit

Yes, the camera calibration process expects the chessboard pattern to be completely flat.

Eduardo gravatar imageEduardo ( 2017-07-17 04:28:22 -0500 )edit

I updated the question, now I have modified the program to takes images instead video stream, also now I am using a flat pattern, and I change fisheye::distortImage by remap function but the result still looks wrong

RdlP gravatar imageRdlP ( 2017-07-17 05:58:03 -0500 )edit