PublicationDetail

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

M. Slavcheva, M. Baust, S. Ilic
Towards Implicit Correspondence in Signed Distance Field Evolution
PeopleCap Workshop, IEEE International Conference on Computer Vision (ICCVW), Venice, Italy, October 2017 (bib)

The level set framework is widely used in geometry processing due to its ability to handle topological changes and the readily accessible shape properties it provides, such as normals and curvature. However, its major drawback is the lack of correspondence preservation throughout the level set evolution. Therefore, data associated with the surface, such as colour, is lost. The objective of this paper is a variational approach for signed distance field evolution which implicitly preserves correspondences. We propose an energy functional based on a novel data term, which aligns the lowest-frequency Laplacian eigenfunction representations of the input and target shapes. As these encode information about natural deformations that the shape can undergo, our strategy manages to prevent data diffusion into the volume. We demonstrate that our system is able to preserve texture throughout articulated motion sequences, and evaluate its geometric accuracy on public data.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.



Edit | Attach | Refresh | Diffs | More | Revision r1.11 - 19 Jul 2016 - 16:26 - NassirNavab

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif