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Thanks for the great work and sharing the code for other researchers. I am wondering if you have tested this algorithm on registering partially occluded point clouds with templates. Most 3D scanners are only able to get the 3D information of the front-facing surface of the target object. While we normally have full 3D meshes of the target objects. The distribution matching seems to be based on the assumption that the distribution of two related point clouds are the same. Will this matching of two distribution still generate optimal solution in this case?
Thanks,
Lei
The text was updated successfully, but these errors were encountered:
Thanks for the great work and sharing the code for other researchers. I am wondering if you have tested this algorithm on registering partially occluded point clouds with templates. Most 3D scanners are only able to get the 3D information of the front-facing surface of the target object. While we normally have full 3D meshes of the target objects. The distribution matching seems to be based on the assumption that the distribution of two related point clouds are the same. Will this matching of two distribution still generate optimal solution in this case?
Thanks,
Lei
The text was updated successfully, but these errors were encountered: