So, while we work on improving our implementation of image rectification and beyond, let's see what kind of results we can expect from the data we have.
For that, we're going to use a couple of freely available reconstruction tools that already work.
First one is VisualSFV: http://ccwu.me/vsfm/
A GUI application for 3D reconstruction using structure from motion (SFM) from Changchang Wu.
For that we took our stereo video from the last time. Extracted images from the left camera at 5 images per second (extracting images from both cameras was just too many images, and we still don't have them rectified). Used OpenCV and a calibration board to fix the lens distortion and ran it trough VisualSFM.
The result being sparse and dense reconstruction:
And the output in MeshLab:
Once we had the dense reconstruction, we were able to export it from VisualSFM in .cmp format, which can be used as input for the next tool.
Second one is CMPMVS: http://ptak.felk.cvut.cz/sfmservice/websfm.pl?menu=cmpmvs
A multi-view reconstruction software.
So after letting it do all the work, we ended up with the model:
The results are promising, but there is a lot of noise in the reconstruction. Looked closely there are differences in disparity where there are houses, but just. The details like cars are lost.
Looking at single video frames, the images still look slightly blurry. Even though the plane vibrates a lot less now, maybe taking images for reconstruction as video is not the best method.
Time to take some real photos and try with that.
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