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General / Re: Import Laserscan data -registration lost
« on: January 23, 2021, 07:07:00 PM »
Thanks for putting together the example data set Dieter and I agree with the other posts that the laser scan support as currently implemented is not very useful.
I think the current approach of attempting to find and match key points in a panorama representation of a laser scan is also fundamentally limited. Compared to a photo, even high resolution scans are fairly low resolution making the task difficult. Furthermore, many scans are done without color so key points that are identified in IR reflectance may not correspond to ones in color images. If scans are captured with color, that means an additional calibration between the scanner's internal camera and it's measured 3D points, which may introduce an additional source of error.
I think it would be much better to follow an approach similar to what is described in the paper:
A Fast and Robust Framework for Semiautomatic and Automatic Registration of Photographs to 3D Geometry
which describes an algorithm for using known 3D geometry to refine the estimated external and internal camera parameters. This would be a much more general solution and would eliminate many of the limitations of the current implementation.
I think the current approach of attempting to find and match key points in a panorama representation of a laser scan is also fundamentally limited. Compared to a photo, even high resolution scans are fairly low resolution making the task difficult. Furthermore, many scans are done without color so key points that are identified in IR reflectance may not correspond to ones in color images. If scans are captured with color, that means an additional calibration between the scanner's internal camera and it's measured 3D points, which may introduce an additional source of error.
I think it would be much better to follow an approach similar to what is described in the paper:
A Fast and Robust Framework for Semiautomatic and Automatic Registration of Photographs to 3D Geometry
which describes an algorithm for using known 3D geometry to refine the estimated external and internal camera parameters. This would be a much more general solution and would eliminate many of the limitations of the current implementation.