@string{acivs="Proceedings of Advanced Concepts for Intelligent Vision Systems"}
@string{springer="Springer"}
@InProceedings{Kormoczi-Kato2017,
  author    = {Kormoczi, Laszlo and Kato, Zoltan},
  title     = {Filling Missing Parts of a 3D Mesh by Fusion of Incomplete 3D Data},
  booktitle = acivs,
  year      = {2017},
  address   = {Antwerp, Belgium},
  month     = sep,
  publisher = {springer},
  abstract  = {This paper deals with the problem of fusing different (potentially partial) 3D meshes to fill in missing parts (holes) of an accurate reference 3D model using a less accurate but more complete moving 3D model. Typically, accurate 3D models can be produced by range devices (Lidar) which is often limited in setting viewpoints, while traditional Structure from Motion methods are using 2D images which are less restricted in viewpoints, but overall produce a less accurate 3D mesh. Combining the advantages of both modalities is an appealing solution to many real world problems. Herein we propose a novel method which detects holes in the accurate reference mesh and then each hole is filled from the less accurate 3D mesh by gradually estimating local affine transformations around the hole's boundary and propagating it into the inner part. Experimental validation is done on a large real dataset, which confirms the accuracy and reliability of the proposed algorithm.},
}