In this paper, we propose a novel data-driven method that uses a machine learning scheme for formulating fracture simulation with the Boundary Element Method (BEM) as a regression problem. With this method, the crack-opening displacement (COD) of every correlation node is predicted at the next frame … Continue reading “Data-Driven Approach for Simulating Brittle Fracture Surfaces”
Category: Machine Learning
Data-driven Subspace Enrichment for Elastic Deformations with Collisions
We propose an efficient data-driven enrichment approach to adaptively enhance the expressivity of subspaces for elastic deformations with novel collisions. In general, subspace integration method (also known as model reduction) for elastic deformations can greatly increase simulation speed. However, … Continue reading “Data-driven Subspace Enrichment for Elastic Deformations with Collisions”
Data-Driven Detailed Hair Animation for Game Characters
We propose a data-driven method to realize high quality detailed hair animations in interactive applications like games. By devising an error metric method to evaluate hair animation similarities, we take hair features into consideration as much as possible. We also propose a novel database construc … Continue reading “Data-Driven Detailed Hair Animation for Game Characters”