Visual Computing

University of Konstanz
Peer reviewed proceedings of Digital Landscape Architecture 2014 at ETH Zurich

Adaptive Billboard Clouds for Botanical Tree Models

J. Kratt, L. Coconu, T. Dapper, J. Schliep, P. Paar, O. Deussen
Teaser of Adaptive Billboard Clouds for Botanical Tree Models

Material

Paper (.pdf, 609.6KB)

Abstract

We present a framework for automatic Level-of-Detail control of botanical tree models based on hierarchical billboard clouds. These clouds react to quality measures developed specifically for plant models. They are optimized for providing minimum visual differences compared to the full polygonal models. The tree structure is analyzed to determine the geometric parts of the tree that are substituted by billboards. By computing the implicit surface of the tree model we can efficiently determine the average occlusion of each area within a tree that is used to guide the substitution. Our system is validated by comparing simplified versions of different trees with their full polygonal models. We realized our system as plug-in for MAXON CINEMA 4D.

BibTeX

@inproceedings{Kratt2014AdaptiveBillboardClouds,
  address   = {Berlin},
  author    = {J. Kratt, L. Coconu, T. Dapper, J. Schliep, P. Paar, O. Deussen},
  booktitle = {Peer reviewed proceedings of Digital Landscape Architecture 2014 at ETH Zurich},
  editor    = {Hayek, Wissen},
  isbn      = {978-3-87907-530-0},
  pages     = {274--282},
  publisher = {Wichmann},
  title     = {Adaptive Billboard Clouds for Botanical Tree Models},
  url       = {http://graphics.uni-konstanz.de/publikationen/Kratt2014AdaptiveBillboardClouds},
  year      = {2014}
}