| dc.description.abstract | Synthetically generated terrain models are useful across a broad range of applications, including computer
generated art & animation, virtual reality and gaming, and architecture. Existing algorithms for terrain
generation suffer from a number of problems, especially that of being limited in the types of terrain that
they can produce and of being difficult for the user to control. Typical applications of synthetic terrain
have several factors in common: first, they require the generation of large regions of believable (though not
necessarily physically correct) terrain features; and second, while real-time performance is often needed
when visualizing the terrain, this is generally not the case when generating the terrain.
In this thesis, I present a new, design-by-example method for synthesizing terrain height fields. In this
approach, the user designs the layout of the terrain by sketching out simple regions using a CAD-style
interface, and specifies the desired terrain characteristics of each region by providing example height fields
displaying these characteristics (these height fields will typically come from real-world GIS data sources).
A height field matching the user's design is generated at several levels of detail, using a genetic algorithm to
blend together chunks of elevation data from the example height fields in a visually plausible manner.
This method has the advantage of producing an unlimited diversity of reasonably realistic results, while
requiring relatively little user effort and expertise. The guided randomization inherent in the genetic
algorithm allows the algorithm to come up with novel arrangements of features, while still approximating
user-specified constraints. | en |
