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Efficient Procedural Generation of Forests.

Authors: Kenwood, Julian; Gain, James; Marais, Patrick;

Efficient Procedural Generation of Forests.

Abstract

Forested landscapes are an important component of many large virtual environments in games and film. In order to reduce modelling time, procedural methods are often used. Unfortunately, procedural tree generation tends to be slow and resource-intensive for large forests. The main contribution of this paper is the development of an efficient procedural generation system for the creation of large forests. Our system uses L-systems, a grammar-based procedural technique, to generate each tree. We algorithmically modify L-system tree grammars to intelligently use an instance cache for tree branches. Our instancing approach not only makes efficient use of memory but also reduces the visual repetition artifacts which can arise due to the granularity of the instances. Instances can represent a range of structures, from a single branch to multiple branches or even an entire tree. Our system improves the speed and memory requirements for forest generation by 3–4 orders of magnitude over naïve methods: we generate over 1;000;000 trees in 4.5 seconds, while using only 350MB of memory.

Country
Czech Republic
Keywords

procedural tree generation, L-systems, instancing, virtual environments, L-systémy, virtuální prostředí, procedurální generování stromů

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citations
The total number of citations received by all articles of the researcher of interest.
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green