Automatic matching result issue about direct_visual_lidar_calibration

[koide3]

1. Because we were interested in creating colored point clouds, we chose projecting image data onto the point cloud. I thinks a visualization with the opposite projection easily be realized using, for example, rviz.

2. Because the image-point-cloud alignment algorithm works on intensity data, we convert images into mono8. Meanwhile, I think some minor modification makes it possible to show colored images.

3. The result of ouster looks corrupted. Did you enable dynamic point cloud integration?

4. The environment itself contains rich geometrical features and looks good, but make sure that there is no dynamic objects.

5. The accumulated point cloud is too sparse to extract features. I recommend take a longer data with more movement to generate a dense point cloud.