Closed chenkangjie1123 closed 4 months ago
It is difficult to find a great angle
Since each scene has a different scale, the figure generation requires a bit of manual tweaking when you use it for a new scene. You'll have to adjust the far clipping plane to only render the correct region of space, then pick a good-looking angle for the point cloud. You can adjust these things here:
SCENES = (
# scene, context 1, context 2, far plane
# ("fc60dbb610046c56", 28, 115, 10.0),d7c9abc0b221c799
# ("1eca36ec55b88fe4", 0, 120, 3.0, [110]), # teaser fig.
("2c52d9d606a3ece2", 87, 112, 35.0, [105]),
("71a1121f817eb913", 139, 164, 10.0, [65]),
("d70fc3bef87bffc1", 67, 92, 10.0, [60]),
("f0feab036acd7195", 44, 69, 25.0, [125]),
("a93d9d0fd69071aa", 57, 82, 15.0, [60]),
)
In general, I found that indoor scenes with large furniture objects and walls on 2 sides (rather than 3) look best and highlight the 3D-ness of the point cloud the most.
Thank you very much for your reply. I have successfully experimented this morning. This angle parameter is indeed difficult to adjust, and the quality of different scenes varies greatly.
Hello, the point cloud visualization image in your paper is very beautiful. How was it drawn? I tried to use the generate_point_cloud_figure.py file in the code to draw it, but the results were quite different.
The following is drawn by generate_point_cloud_figure.py
The following is the corresponding scenario