# Parallel Reconstruction of Quad Only Meshes from Volume Data

Zint D, Grosso R (2020)

**Publication Language:** English

**Publication Type:** Conference contribution, Conference Contribution

**Publication year:** 2020

**Publisher:** SciTePress

**Pages Range:** 102-112

**Conference Proceedings Title:** Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP

**Event location:** Valletta

**ISBN:** 978-989-758-402-2

**DOI:** 10.5220/0008948701020112

### Abstract

We present a method to reconstruct quad only meshes from volume data which mainly consists of two steps: reconstruction of a quad only mesh and topological simplification to reduce the number of irregular vertices. A novel algorithm is described that computes Dual Marching Cubes (DMC) meshes without using lookup tables. The meshes are topologically consistent across cell borders, i.e. they are watertight. The output of the algorithm is a quad only mesh stored in a halfedge data structure. Due to the transitions between voxel layers in volume data, meshes have numerous quad elements with vertices of valence 3-X-3-Y, where X;Y ≥ 5, and 3-3-3-3. Hence, we simplify the mesh by eliminating these elements wherever possible. Finally, we briefly describe a CUDA implementation of the algorithms, which allows processing huge amounts of data on GPU at almost interactive time rates.

### Authors with CRIS profile

### How to cite

**APA:**

Zint, D., & Grosso, R. (2020). Parallel Reconstruction of Quad Only Meshes from Volume Data. In INSTICC (Eds.), *Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: GRAPP* (pp. 102-112). Valletta, MT: SciTePress.

**MLA:**

Zint, Daniel, and Roberto Grosso. "Parallel Reconstruction of Quad Only Meshes from Volume Data." *Proceedings of the 15th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Valletta* Ed. INSTICC, SciTePress, 2020. 102-112.

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