한국컴퓨터그래픽스학회논문지 (Journal of the Korea Computer Graphics Society)

  • 제29권4호
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  • Pages.17-24
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  • 2023
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  • 1975-7883(pISSN)
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  • 2383-529X(eISSN)
한국컴퓨터그래픽스학회 (Korea Computer Graphics Society)
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SDF를 이용한 자동 스키닝 웨이트 페인팅 신경망

Neural network for automatic skinning weight painting using SDF

  • 설효석 (한양대학교 일반대학원 컴퓨터소프트웨어학과) ;
  • 권태수 (한양대학교 일반대학원 컴퓨터소프트웨어학과)
  • Hyoseok Seol (Dept. of Computer and Software, Hanyang University) ;
  • Taesoo Kwon (Dept. of Computer and Software, Hanyang University)
  • 투고 : 2023.06.29
  • 심사 : 2023.08.16
  • 발행 : 2023.09.01
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초록

컴퓨터 그래픽스 및 컴퓨터 비전 분야의 발전에 따라 삼차원 물체를 다양한 표현 방식으로 나타내고 있다. 이에 따라 여러 표현 방식을 사용하는 캐릭터의 애니메이션 제작에 대한 수요 또한 증가하고 있다. 캐릭터 애니메이션 제작에 주로 사용되는 스켈레탈 애니메이션의 경우 캐릭터 표면이 어느 관절로부터 영향을 받는지를 정하는 스키닝 웨이트 페인팅 작업이 필요하다. 본 논문은 삼각형 메시를 비롯한 여러 표현방식으로 나타난 캐릭터에 대한 스키닝 웨이트 페인팅 과정을 자동화하는 방법을 제안한다. 우선 다양한 표현 방식을 사용한 삼차원 캐릭터에 대해 일반적으로 사용할 수 있도록 Signed Distance Field(SDF)를 이용한다. 이후 그래프 신경망과 다층 퍼셉트론 계층 구조를 활용하여 캐릭터 표면 상에 주어진 위치에서의 스키닝 웨이트를 예측할 수 있다.

In computer graphics and computer vision research and its applications, various representations of 3D objects, such as point clouds, voxels, or triangular meshes, are used depending on the purpose. The need for animating characters using these representations is also growing. In a typical animation pipeline called skeletal animation, "skinning weight painting" is required to determine how joints influence a vertex on the character's skin. In this paper, we introduce a neural network for automatically performing skinning weight painting for characters represented in various formats. We utilize signed distance fields (SDF) to handle different representations and employ graph neural networks and multi-layer perceptrons to predict the skinning weights for a given point.

키워드

과제정보

이 성과는 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원을 받아 수행된 연구임(NRF-2020R1A2C1012847).

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