Navigation-Driven Approximate Convex Decomposition
James Andrews
Abstract
Approximate convex decomposition – approximating a shape by a set of convex hulls – is a popular approach to creating efficient collision representations for games and simulations. Existing algorithms to construct such decompositions are typically driven by general surface- or volume-based error metrics that can’t ignore unreachable internal surfaces nor provide local control over the results. We introduce the problem of navigable approximate convex decomposition: First, define a navigable space for the input shape which other objects in the game or simulation must be able to move through, then find a decomposition which does not overlap that space. We show how to automatically find such navigable space, how to customize it, and we introduce an approximate convex decomposition algorithm that protects it. Our results demonstrate that this approach can generate decompositions that meet application requirements faster and with fewer convex hulls than previous methods, while providing a new level of flexibility in defining what those requirements are.
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- Approximate convex decomposition for 3D meshes with collision-aware concavity and tree searchXinyue Wei, Minghua Liu, Zhan Ling, Hao SuSIGGRAPH 2022 · 79 citations
- CvxNet: Learnable Convex DecompositionBoyang Deng, Kyle Genova, Soroosh Yazdani, Sofien Bouaziz et al.CVPR 2020
- SAPIEN: A SimulAted Part-Based Interactive ENvironmentFanbo Xiang, Yuzhe Qin, Kaichun Mo, Yikuan Xia et al.CVPR 2020
- BSP-Net: Generating Compact Meshes via Binary Space PartitioningZhiqin Chen, Andrea Tagliasacchi, Hao ZhangCVPR 2020
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