Detected Corners from point clouds and monocular camera can not match about ilcc

[Rockyzyk]

I changed the first detection point to “lower left” in the image, and it works! Thanks so much for help!

[Rockyzyk]

I just received you reply! Thanks a lot!
Perhaps, the first detection point is mean reason as we though. I will check now!

[mfxox]

It's highly possible that 3D corners may not be correctly detected due to a wrong detection of chessboard' point cloud.

Can you check whether 3D corners were correctly detected with the following code?

    from ILCC import utility
    utility.vis_ested_pcd_corners(ind=1)

And how many image-pcd pairs did you use?

[Rockyzyk]

Thanks for reply and answer! Here is my figure after running the code:
from ILCC import utility
utility.vis_ested_pcd_corners(ind=1)

I think it can detect chessboard correctly.

My image-pcd pairs is 7 pairs, but the chessboard doesn't move, which is in same relative position between camera and VLP16 in these 7 pairs. it is OK?
And could you please explain more about jdc_thre_ratio and agglomerative_cluster_th_ratio in config.yaml. What is their scope? And how should I adjust them in this situation?

[mfxox]

From the image you uploaded, both the point cloud of chessboard and 3D corners are correctly detected as you thought.
I just noticed that the counting order of corners on the image differs from the request for running the program.
This will cause the mis-correspondence between image-pcd corners and further cause the failure of the optimization.
Currently, the counting order of 2D and 3D corners obeys to the rule: 1. starts from the lower left; 2. counts from lower left to upper right with the zigzag order.
You can check a sample image shown here.
Can you try to reorder the image corners and run the optimization again?

I am not sure why you didn't move the chessboard in 7 pairs. If you don' t change the relative position/pose of the chessboard to increase variation, what is the meaning to increase the image-pcd pairs.

As for jdc_thre_ratio and agglomerative_cluster_th_ratio, they relate to the segmentation of the point cloud to get the chessboard. As the chessboard seems to be segmented correctly, I think it's fine of these two parameters for your situation.

[Rockyzyk]

By the way, I use OpenCV the detect image corners, and the first point is not “lower left” is “lower right”, maybe that is the reason, I will try to fix it and reply you.
Furthermore, the setting of corner size for OpenCV is different with MATLAB. For example, your checkboard size is (8,6) for MATLAB but is should be changed to (7,5) in OpenCV. I found the code doesn't deal with it. If you have time, you can fix it!

[nonlinear1]

@Rockyzyk I found that your checkerboard is different from the one which is given by mfxox. I think the program must changed according to your new partern checkerboard. And Could you tell me how can change your program? I was faced the same problem and I want change a different checkerboard different from the one given by mfxox. Thank you very much!