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Real-Time Tree Rendering

Authors: Inmaculada Remolar; Cristina Rebollo; Miguel Chover; José Ribelles;

Real-Time Tree Rendering

Abstract

Interactive rendering of outdoor scenes is currently one of the most important challenges in computer graphics. This article presents a new method of real-time visualization of trees and plants that combines both multiresolution modeling techniques and the dynamic generation of impostors. In our method, trees and plants are represented by continuous view-dependent levels of detail. This enables us to represent many complex tree models with variable resolution. The number of primitives rendered per tree is reduced according to their importance in the scene without loss of leafiness. Furthermore, trees are visualized using dynamic impostors that take advantage of the frame-to-frame coherence inherent in tree-dimensional scenes. The impostors avoid the need to redraw all the geometry of the scene continuously. This method permits visualization of outdoor scenes with a high number of trees in interactive applications such as computer games or virtual reality, adapting the level of detail to the capability of graphic systems.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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!
5
Average
Top 10%
Average
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