ML Anthology

Fractal Surface Reconstruction for Modeling Natural Terrain

Kenichi Arakawa, Eric Krotkov
CVPR 1993 pp. 314-320
doi:10.1109/CVPR.1993.340963 /cvpr/1993/arakawa1993cvpr-fractal/

Abstract

A surface reconstruction method is developed, based on fractal geometry, for modeling natural terrain. The method estimates dense surfaces from sparse data located in any configuration while preserving roughness. A redefinition of the temperature parameter in the stochastic regularization method is presented. It plays a critical role in controlling roughness as a function of the fractal dimension. The fractalness of surfaces reconstructed with the temperature parameter is evaluated qualitatively by applying a technique for fractal dimension estimation. As a result, it is possible to reconstruct rugged natural surfaces which preserve the original roughness from sparse data sensed by, for example, scanning laser rangefinders.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

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Cite

Text

Arakawa and Krotkov. "Fractal Surface Reconstruction for Modeling Natural Terrain." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993. doi:10.1109/CVPR.1993.340963

Markdown

[Arakawa and Krotkov. "Fractal Surface Reconstruction for Modeling Natural Terrain." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1993.](https://mlanthology.org/cvpr/1993/arakawa1993cvpr-fractal/) doi:10.1109/CVPR.1993.340963

BibTeX

@inproceedings{arakawa1993cvpr-fractal,
  title     = {{Fractal Surface Reconstruction for Modeling Natural Terrain}},
  author    = {Arakawa, Kenichi and Krotkov, Eric},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1993},
  pages     = {314-320},
  doi       = {10.1109/CVPR.1993.340963},
  url       = {https://mlanthology.org/cvpr/1993/arakawa1993cvpr-fractal/}
}