Recently I’m checking the way to bring the image masks features back to the latest ODM version. It’s still working in opensfm stage, but not for dense point cloud and later stages. I’ve made some progress to implement a script to filter the dense point cloud by masks. The approach is the same as the one used in MVE, it iterates through each shot, projects all vertices to that camera, and removes vertices locate inside the mask area. The filtered point clouds from both approaches are similar. I might need to optimize it as it’s implemented in python and could be slow for large datasets.
However, while I move on to check the mesh reconstruction results. I noticed that the new and old version of PoissonRecon provides different results. The old reconstruction is like the first 2 images, the new reconstruction is like the last 2 images. While the old reconstruction fills the filtered holes with smooth and flat faces, the new reconstruction fills with bowl-shaped faces.
I wonder if we can tweak the arguments for PoissonRecon to make it have similar results to the old version? (I’m not familiar with PoissonRecon, hope I can find help here)