Detalhes bibliográficos
Ano de defesa: |
2018 |
Autor(a) principal: |
Oe, Nicolas Masanori Shimizu |
Orientador(a): |
Não Informado pela instituição |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Dissertação
|
Tipo de acesso: |
Acesso aberto |
Idioma: |
eng |
Instituição de defesa: |
Biblioteca Digitais de Teses e Dissertações da USP
|
Programa de Pós-Graduação: |
Não Informado pela instituição
|
Departamento: |
Não Informado pela instituição
|
País: |
Não Informado pela instituição
|
Palavras-chave em Português: |
|
Link de acesso: |
http://www.teses.usp.br/teses/disponiveis/55/55134/tde-02012019-142426/
|
Resumo: |
In this work, its 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, its 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. |