Voxel Graph Operators: Topological Voxelization, Graph Generation, and Derivation of Discrete Differential Operators from Voxel Complexes
Pirouz Nourian, Shervin Azadi

TL;DR
This paper introduces a fast, topologically accurate workflow for converting vector models into voxel representations, constructing connectivity graphs, and deriving differential operators for spatial analysis and physics simulations.
Contribution
It presents novel algorithms for topological voxelization, graph construction, and discretization of differential operators from voxel complexes, ensuring topological and geometrical validity.
Findings
Reversible topological voxelization mapping from 3D models to index space.
Algorithms for constructing connectivity graphs and hyper-graphs on voxel data.
Discretization of differential and integral operators for PDEs and physics simulations.
Abstract
In this paper, we present a novel workflow consisting of algebraic algorithms and data structures for fast and topologically accurate conversion of vector data models such as Boundary Representations into voxels (topological voxelization); spatially indexing them; constructing connectivity graphs from voxels; and constructing a coherent set of multivariate differential and integral operators from these graphs. Topological Voxelization is revisited and presented in the paper as a reversible mapping of geometric models from to to and eventually to an index space created by Morton Codes in while ensuring the topological validity of the voxel models; namely their topological thinness and their geometrical consistency. In addition, we present algorithms for constructing graphs and hyper-graph connectivity models on voxel data for…
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Taxonomy
TopicsTopological and Geometric Data Analysis · Data Visualization and Analytics · Data Management and Algorithms
