Interactive Design of Probability Density Functions for Shape Grammars

• Presented at: ACM SIGGRAPH Asia Conference
• Published in: Acm Transactions On Graphics (ISSN: 0730-0301), vol. 34, num. 6, p. 206
• New York: Assoc Computing Machinery, 2015

A shape grammar defines a procedural shape space containing a variety of models of the same class, e.g. buildings, trees, furniture, airplanes, bikes, etc. We present a framework that enables a user to interactively design a probability density function (pdf) over such a shape space and to sample models according to the designed pdf. First, we propose a user interface that enables a user to quickly provide preference scores for selected shapes and suggest sampling strategies to decide which models to present to the user to evaluate. Second, we propose a novel kernel function to encode the similarity between two procedural models. Third, we propose a framework to interpolate user preference scores by combining multiple techniques: function factorization, Gaussian process regression, auto-relevance detection, and l(1) regularization. Fourth, we modify the original grammars to generate models with a pdf proportional to the user preference scores. Finally, we provide evaluations of our user interface and framework parameters and a comparison to other exploratory modeling techniques using modeling tasks in five example shape spaces: furniture, low-rise buildings, skyscrapers, airplanes, and vegetation.

Keywords: procedural modeling ; interactive design ; regression ; preference elicitation ; active learning

Reference

• EPFL-CONF-213964
• doi:10.1145/2816795.2818069
• View record in Web of Science

Record created on 2015-12-02, modified on 2017-05-12