This paper presents a novel interface for generating procedural models,
textures, and other content, motivated by the need for interfaces that are
simpler to understand and more rapidly utilize. Instead of directly manipulating
procedural parameters, users specify adjectives that describe the content to be
generated. By making use of a training corpus and semantic information from the
WordNet database, our system is able to map from the set of all possible
descriptions, adjective space, to the set of all combinations of procedural
parameters, parameter space. This is achieved through a modification to radial
basis function networks, and the application of particle swarm optimization to
search for suitable solutions. By testing with three very different procedural
generation systems, we demonstrate the wide applicability of this approach. Our
results show that non-technical users not only prefer an adjectival interface to
one offering direct control over the procedural parameters, but also produce
content that more closely matches a given target