: In procedural modeling, a single rule set can produce a wide variety of 3D models (left). This paper presents a thumbnail gallery generation system which automatically samples a rule set, clusters the resulting models into distinct groups (middle), and selects a representative image for each group to visualize the diversity of the rule set (right). Procedural modeling allows for the generation of innumerable variations of models from a parameterized, conditional or stochastic rule set. Due to the abstractness, complexity and stochastic nature of rule sets, it is often very difficult to have an understanding of the diversity of models that a given rule set defines. We address this problem by presenting a novel system to automatically generate, cluster, rank, and select a series of representative thumbnail images out of a rule set. We introduce a set of 'view attributes' that can be used to measure the suitability of an image to represent a model, and allow for comparison of different models derived from the same rule set. To find the best thumbnails, we exploit these view attributes on images of models obtained by stochastically sampling the parameter space of the rule set. The resulting thumbnail gallery gives a representative visual impression of the procedural modeling potential of the rule set. Performance is discussed by means of a number of distinct examples and compared to state-of-the-art approaches.
In the context of procedural modeling, REF propose a strategy to sample a procedural space to generate representative thumbnail images.
Thumbnail galleries for procedural models
Comput. Graph. Forum
Comput. Graph. Forum
Computer Science