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Camera calibration parameters #6
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hi, you can check this webpage for visualization: https://struct002.github.io/PKUMMD/ |
I'm sorry, but I did not find the calibration parameters, nor visualization code on the mentioned webpage. Could you specify what you meant by visualization? |
Hi, we include a camera matrix M in FAQ parts, but I am not sure where to get a matrix for each camera. I am double-checking this with my team since I already graduated. Thanks |
Seems that we have 3 different sets of skeleton joints and depth/RGB images for each camera. Using M can map the skeleton joints to image coordinates, so M can be used for all three camera. Please note that we don't have real-world 3D coordinates for skeleton joints. |
So I guess, since you don't have the intrinsic (focal length and principal point) and extrinsic (rotation matrix and translation vector) parameters of your camera, I won't be able to get point clouds in real-world coordinates from your depth data. |
Well, the M I mentioned before is the camera intrinsic matrix. As for the extrinsic matrix, it is hard to obtain that as we slightly changed the camera position during capturing (for different sequences). So if you want to project the 3D points cloud, for the first view you can simply use M[I|0], but you need to estimate the R and t for the second and third view, sorry. |
wait, that intrinsic matrix is from RGB camera, let me see if I can get that from Depth camera |
Hi, the M you provided on https://struct002.github.io/PKUMMD/ was for the RGB cameras. Since I'm trying to project the camera-space 3D coordinates on to the respective depth images, I would rather need the intrinsic matrix for the depth cameras. I wonder how I can get them? Thanks for maintaining this dataset btw, it's hugely helpful for my thesis |
Hi,
I'm wondering if you are able to provide your kinect v2 calibration parameters, since I'd like to produce point clouds from the dataset depth images.
Thank you.
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