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Billboard Clouds for Extreme Model Simplification

Xavier Décoret 1 Frédo Durand 1, * François X. Sillion 2 Julie Dorsey 3
* Corresponding author
2 ARTIS - Acquisition, representation and transformations for image synthesis
GRAVIR - IMAG - Laboratoire d'informatique GRAphique, VIsion et Robotique de Grenoble, Inria Grenoble - Rhône-Alpes, CNRS - Centre National de la Recherche Scientifique : FR71
Abstract : We introduce billboard clouds -- a new approach for extreme simplification in the context of real-time rendering. 3D models are simplified onto a set of planes with texture and transparency maps. We present an optimization approach to build a billboard cloud given a geometric error threshold. After computing an appropriate density function in plane space, a greedy approach is used to select suitable representative planes. A good surface approximation is ensured by favoring planes that are ``nearly tangent'' to the model. This method does not require connectivity information, but instead avoids cracks by projecting primitives onto multiple planes when needed. For extreme simplification, our approach combines the strengths of mesh decimation and image-based impostors. We demonstrate our technique on a large class of models, including smooth manifolds and composite objects.
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  • HAL Id : inria-00510175, version 1

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Xavier Décoret, Frédo Durand, François X. Sillion, Julie Dorsey. Billboard Clouds for Extreme Model Simplification. Proceedings of the ACM Siggraph, 2003, San diego, United States. ⟨inria-00510175⟩

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