Fast Tetrahedral Meshing in the Wild

08/09/2019
∙
by   Yixin Hu, et al.
∙
0
∙

We propose a new tetrahedral meshing technique, fTetWild, to convert triangle soups into high-quality tetrahedral meshes. Our method builds upon the TetWild algorithm, inheriting its unconditional robustness, but dramatically reducing its computation cost and guaranteeing the generation of a valid tetrahedral mesh with floating point coordinates. This is achieved by introducing a new problem formulation, which is well suited for a pure floating point implementation and naturally leads to a parallel implementation. Our algorithm produces results qualitatively and quantitatively similar to TetWild, but at a fraction of the computational cost, with a running time comparable to Delaunay-based tetrahedralization algorithms.

READ FULL TEXT

Please sign up or login with your details

Continue with:
Or login with email
Enter Password
Re-enter Password

Forgot password? Click here to reset
Success!
Error Icon An error occurred

Sign in with Google

×

Use your Google Account to sign in to DeepAI

×
Pro

Consider DeepAI Pro

Subscribe to DeepAI Pro
DeepAI Pro
Provides a limited generation allowance each month. When exceeded, you are charged overage rates available at deepai.org/pricing. Also includes an ad-free experience and API access. Renews automatically until canceled. Non-refundable.
Subtotal
Total due today

Payment

Add DeepAI credits
DeepAI credits
One-time purchase. Credits are added to your wallet after payment.
Subtotal
Total due today

Payment