admin管理员组

文章数量:1613385

If you are using one of the calibration images, then all the information you need is in the cameraParams object.

Let's say you are using calibration image 1, and let's call it I.First, undistort the image:

I = undistortImage(I, cameraParams);

Get the extrinsics (rotation and translation) for your image: 

R = cameraParams.RotationMatrices(:,:,1);
t = cameraParams.TranslationVectors(1, :);

Then combine rotation and translation into one matrix:

R(3, :) = t;

Now compute the homography between the checkerboard and the image plane:

H = R * cameraParams.IntrinsicMatrix;

Transform the image using the inverse of the homography:

J = imwarp(I, projective2d(inv(H)));
imshow(J);

You should see a "bird's eye" view of the checkerboard. If you are not using one of the calibration images, then you can compute R and t using the extrinsics function.

Another way to do this is to use detectCheckerboardPoints and generateCheckerboardPoints, and then compute the homography using fitgeotform.

本文标签： VisioncomputerCalculateMatrixfundamental

版权声明：本文标题：computer vision-calculate fundamental matrix 内容由热心网友自发贡献，该文观点仅代表作者本人， 转载请联系作者并注明出处：https://m.elefans.com/dianzi/1728643291a1167385.html， 本站仅提供信息存储空间服务，不拥有所有权，不承担相关法律责任。如发现本站有涉嫌抄袭侵权/违法违规的内容，一经查实，本站将立刻删除。