Deep Points Consolidation
ACM Transactions on Graphics (Proceedings of SIGGRAPH Asia 2015), to appear
| University of Bern
||Shenzhen VisuCA Key Lab/SIAT
||Memorial University of Newfoundland
||University of Bern
||Tel Aviv University
In this paper, we present a consolidation method that is based on a new representation of 3D point sets. The key idea is to augment each surface point into a deep point by associating it with an inner point that resides on the meso-skeleton, which consists of a mixture of skeletal curves and sheets. The deep points representation is a result of a joint optimization applied to both ends of the deep points. The optimization objective is to fairly distribute the end points across the surface and the meso-skeleton, such that the deep point orientations agree with the surface normals. The optimization converges where the inner points form a coherent meso-skeleton, and the surface points are consolidated with the missing regions completed. The strength of this new representation stems from the fact that it is comprised of both local and non-local geometric information. We demonstrate the advantages of the deep points consolidation technique by employing it to consolidate and complete noisy point-sampled geometry with large missing parts.
This work was supported in part by NSFC (61522213, 61232011, 61379090), 973 Program (2014CB360503), 863 Program (2015AA016401), Guangdong Science and Technology Program (2015A030312015, 2014B050502009, 2014TX01X033), Shenzhen VisuCA Key Lab (CXB201104220029A), NSERC (293127) and BSF (2012376).