Billboard Clouds

Abstract : We introduce billboard clouds -- a new approach for extreme simplification. 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 very good surface approximation is ensured by favoring planes that are «nearly tangent» to the model. This method does not require connectivity information, but still avoids cracks by projecting primitives onto multiple planes when needed. The technique is quite flexible through the appropriate choice of error metrics, which can include image-space or object-space deformation, as well as any application-dependent objective function. It is fully automatic and controlled by two intuitive user-supplied parameters. 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, as well as entire scenes containing buildings and vegetation.
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Submitted on : Tuesday, May 23, 2006 - 7:48:05 PM
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  • HAL Id : inria-00072103, version 1

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Xavier Décoret, Frédo Durand, François X. Sillion, Julie Dorsey. Billboard Clouds. [Research Report] RR-4485, INRIA. 2002. ⟨inria-00072103⟩

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