Boundary particle resampling for surface reconstruction in particle-based fluids
Nicolas Masanori Shimizu Oe · 2019
In this work, it's presented a novel particle resampling method for free-surface fitting of liquids from particle-based fluid simulations.The proposed approach is simple and easy to implement, and only requires the positions of the particles to properly identify and refine regions with small-scale features.The method comprises three main stages: boundary detection, feature classification, and particle refinement.For each simulation frame, firstly the free-surface is captured through a boundary detection scheme as chosen by the user.Then, the boundary particles are classified and labeled according to the deformation and the stretching of the freesurface computed from the Principal Component Analysis (PCA) of the particle positions.Finally, particles placed at feature regions are refined according to their feature classification.In order to render the free-surface, it's demonstrated how the traditional methods of free-surface fitting in Computer Graphics and Computational Physics literature can be benefited by the proposed resampling method.Moreover, the results shown in this work attest the effectiveness and robustness of the method when compared against state-of-the-art adaptive particle sampling techniques.