Bijective Volumetric Mapping via Star Decomposition

A method for the construction of bijective volumetric maps between 3D shapes is presented. Arbitrary shapes of ball-topology are supported, overcoming restrictions of previous methods to convex or star-shaped targets. In essence, the mapping problem is decomposed into a set of simpler mapping problems, each of which can be solved with previous methods for discrete star-shaped mapping problems. Addressing the key challenges in this endeavor, algorithms are described to reliably construct structurally compatible partitions of two shapes with constraints regarding star-shapedness and to compute a parsimonious common refinement of two triangulations.

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Publication Details

Journal
ACM Transactions on Graphics
Published
2024-11-19
DOI
https://doi.org/10.1145/3687950
Citations
4
Primary Topic
Advanced Vision and Imaging
Type
article
Field-Weighted Citation Impact
1.00

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article

Bijective Volumetric Mapping via Star Decomposition

Steffen Hinderink, Marcel Campen, Hendrik Brückler
4 citations
ACM Transactions on Graphics
Advanced Vision and Imaging
1.00
article

Bijective Volumetric Mapping via Star Decomposition

Steffen Hinderink, Marcel Campen, Hendrik Brückler
article en
4 citations

Abstract

A method for the construction of bijective volumetric maps between 3D shapes is presented. Arbitrary shapes of ball-topology are supported, overcoming restrictions of previous methods to convex or star-shaped targets. In essence, the mapping problem is decomposed into a set of simpler mapping problems, each of which can be solved with previous methods for discrete star-shaped mapping problems. Addressing the key challenges in this endeavor, algorithms are described to reliably construct structurally compatible partitions of two shapes with constraints regarding star-shapedness and to compute a parsimonious common refinement of two triangulations.

ACM Transactions on GraphicsVol. 43(6)
Osnabrück University (DE)
Deutsche Forschungsgemeinschaft
Sustainable cities and communities
Openalex Percentile: Top 22%
Advanced Vision and Imaging
1.00
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