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.<>
Fractal surface reconstruction for modeling natural terrain
1993-01-01
550358 byte
Conference paper
Electronic Resource
English
Fractat Modeling of Natural Terrain: Analysis and Surface Reconstruction with Range Data
British Library Online Contents | 1996
|Evaluation of fractal dimension of soft terrain surface
Online Contents | 2017
|Fractal Dimensions of Terrain Profiles
British Library Conference Proceedings | 1990
|Fractal dimensions of terrain profiles
Automotive engineering | 1990
|Fractal terrain generation for vehicle simulation
Automotive engineering | 2012
|