yulan0215

> hi, > First of all, I want to commend this amazing work. Secondly, this work is of great help to my project. Now I would like to evaluate the...

> Pick around 20-30+ corresponding points to get good results. You can reset the points collected so far by deleting the `img_corners.npy` and `pcl_corners.npy` files. Actually I used about 20...

You mean, check the points and pixels in the .npy file? The file pcl_corner and img_corner?

I checked in the image and pcd, I selected 12 pixels and 2 points in one image and one frame point cloud.... You said use 20 to 30 correspondences by...

> You should select the same corresponding points. Not sure what you mean by 12 pixels and 2 points. Corresponding points means you pick 12 pixels on the image and...

> Don't set your slop too high in the time synchronizer. 0.5 secs should be fine as long as the scene is static for a while and the calibration targets...

> Yes, just delete the npy files once and then for every successive correspondences picked, they will continually be updated. Thank you for your reply and I encountered another issue...

> You can compute the RMSE error at this [point](https://github.com/heethesh/lidar_camera_calibration/blob/master/scripts/calibrate_camera_lidar.py#L341). Here's a rough snippet to get started (untested): > > ``` > > points2D_reproj = cv2.projectPoints(points3D, rotation_vector, translation_vector, camera_matrix, dist_coeffs)[0].squeeze(1)...

> > Hi, I used this code to check rmse but the result was not acceptable for example, the first result was 9 and the second was 27. > >...

> 9 pixel RMSE is reasonable for 6 correspondences, I would recommend to use > 30-40 correspondences. Note that this evaluation computes reprojection error over the outlier points from PnPRansac...