vilem.duha wrote:
Hi, one Idea, did you shoot raw photos?
You can colorcorrect before processing, that might help too. Remember, also when you focus on your subject, your camera actually changes it’s properties.
Yes, you`re right, colorcorrection actually helps, but not too much
Hi Arseniy
So I have inspected the dataset and:
images are NOT in the same positions as the reference dataset for creating XMPs = moved, adjusted camera positions, angles ??
or image names are not correct ? ( image numbering issue ? )
that is why you get BAD reconstruction that is far away from ideal results, as your cameras have different angles from the reference data and it is not possible to use them…
photos of kids are in JPEGs with pretty bad quality ? you did not send me the RAW files…
Arsenyi, some more tips:
try setting in alignment settings image downscale factor to 1
I am in a similar situation, reconstructing some data from a not much rich camera array(only 11 cams).This improved the calibration for me. But I have similar problem, some models are very noisy, while others smooth. It’s a lot about the models skin shininess I think…
Another important parameter is Adaptive blending start in advanced reconstruction settings. It can, If I understand it correctly, determine influence of depth maps, and in case of not having 360 degrees covered, it might improve the coverage. Sadly, by now the parameter can’t go over 0.5. Default is 0.45. Wishgranter, would it be possible to allow higher values for this parameter? Not sure if I understood it right, but by my tests it behaves this way( direction of depthmap vs normal of suface -> depth map is used or not on a certain area).
I am also curious if you find another ways to improve the result.