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Detailed Representation of Liquid-Solid Mixed Surfaces with Adaptive Framework Based Hybrid SDF and Surface Reconstruction

적응형 프레임워크 기반의 하이브리드 부호거리장과 표면복원을 이용한 액체와 고체 혼합 표면의 세밀한 표현

  • Received : 2017.06.25
  • Accepted : 2017.08.31
  • Published : 2017.09.01

Abstract

We propose a new pipeline of fluid surface reconstruction that incorporates hybrid SDF(signed distance fields) and adaptive fluid surface techniques to finely reconstruct liquid-solid mixed surfaces. Previous particle-based fluid simulation suffer from a noisy surface problem when the particles are distributed irregularly. If a smoothing scheme is applied to reduce the problem, sharp and detailed features can be lost by over-smoothing artifacts. Our method constructs a hybrid SDF by combining signed distance values from the solid and liquid parts of the object. We also proposed a method of adaptively reconstructing the surface of the fluid to further improve the overall efficiency. This not only shows the detailed surface of the solid and liquid parts, but also the detail of the solid surface and the smooth fluid surface when both materials are mixed. We introduce the concept of guiding shape and propose a method to get signed distance value quickly. In addition, the hybrid SDF and mesh reconstruction techniques are integrated in the adaptive framework. As a result, our method improves the overall efficiency of the pipeline to restore fluid surfaces.

우리는 액체와 고체가 혼합된 표면을 세밀하게 복원하기 위해 하이브리드 부호거리장과 적응형 유체표면기술을 통합한 유체표면복원의 새로운 파이프라인을 제안한다. 이전 입자기반 유체 시뮬레이션은 입자가 불규칙하게 분포 될 때 유체표면에 노이즈 문제가 발생한다. 이 문제를 줄이기 위해 스무딩(Smoothing)기법을 적용하면 반복적인 스무딩과정으로 인해 선명하고 디테일한 유체의 표면적 특징을 소실하여 유체의 디테일이 사라지는 문제가 발생한다. 우리의 방법은 유체를 구성하는 입자기반의 부호거리값과 고체를 구성하는 삼각형기반의 부호거리값을 결합하여 하이브리드 부호거리장을 구성한다. 그리고 적응적으로 유체의 표면을 복원하는 방법을 제안하여 전체적인 효율성을 한 층 개선시킨다. 이렇게 하면 고체와 액체 부분의 세밀한 표면적 특징을 표현할 수 있을 뿐만 아니라 두 재질이 혼합되었을 때도 디테일한 표면의 특징과 부드러운 유체표면을 모두 나타낼 수 있다. 또한, 가이딩 형상이란 개념을 소개하여 부호거리값을 빠르게 얻어 올 수 있는 방법을 제안한다. 결과적으로, 하이브리드 부호거리장과 메쉬 재복원 기술을 적응형 프레임워크에서 통합함으로써 유체표면을 복원하는 파이프라인의 전반적인 효율성을 개선시켰다.

Keywords

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