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    Interactive design of probability density functions for shape grammars

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    Type
    Conference Paper
    Authors
    Dang, Minh
    Lienhard, Stefan
    Ceylan, Duygu
    Neubert, Boris
    Wonka, Peter cc
    Pauly, Mark
    KAUST Department
    Computer Science Program
    Visual Computing Center (VCC)
    Date
    2015-10-27
    Online Publication Date
    2015-10-27
    Print Publication Date
    2015-10-26
    Permanent link to this record
    http://hdl.handle.net/10754/592887
    
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    Abstract
    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, autorelevance detection, and l1 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.
    Citation
    Interactive design of probability density functions for shape grammars 2015, 34 (6):1 ACM Transactions on Graphics
    Publisher
    Association for Computing Machinery (ACM)
    Conference/Event name
    Proceedings of ACM SIGGRAPH Asia 2015
    DOI
    10.1145/2816795.2818069
    Additional Links
    http://dl.acm.org/citation.cfm?doid=2816795.2818069
    https://youtu.be/ht35WXZwqMM
    Embedded External Content
    ae974a485f413a2113503eed53cd6c53
    10.1145/2816795.2818069
    Scopus Count
    Collections
    Conference Papers; Computer Science Program; Visual Computing Center (VCC)

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