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Automatic Structure Generation using Genetic Programming and Fractal Geometry

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Show simple item record Bergen, Steve 2012-02-09T15:14:03Z 2012-02-09T15:14:03Z 2012-02-09
dc.description.abstract Three dimensional model design is a well-known and studied field, with numerous real-world applications. However, the manual construction of these models can often be time-consuming to the average user, despite the advantages o ffered through computational advances. This thesis presents an approach to the design of 3D structures using evolutionary computation and L-systems, which involves the automated production of such designs using a strict set of fitness functions. These functions focus on the geometric properties of the models produced, as well as their quantifiable aesthetic value - a topic which has not been widely investigated with respect to 3D models. New extensions to existing aesthetic measures are discussed and implemented in the presented system in order to produce designs which are visually pleasing. The system itself facilitates the construction of models requiring minimal user initialization and no user-based feedback throughout the evolutionary cycle. The genetic programming evolved models are shown to satisfy multiple criteria, conveying a relationship between their assigned aesthetic value and their perceived aesthetic value. Exploration into the applicability and e ffectiveness of a multi-objective approach to the problem is also presented, with a focus on both performance and visual results. Although subjective, these results o er insight into future applications and study in the fi eld of computational aesthetics and automated structure design. en_US
dc.language.iso eng en_US
dc.publisher Brock University en_US
dc.subject Aesthetics en_US
dc.subject 3D models en_US
dc.subject Genetic programming en_US
dc.subject L-systems en_US
dc.subject Multi-objective evaluation en_US
dc.title Automatic Structure Generation using Genetic Programming and Fractal Geometry en_US
dc.type Electronic Thesis or Dissertation en_US M.Sc. Computer Science en_US Masters en_US
dc.contributor.department Department of Computer Science en_US Faculty of Mathematics and Science en_US

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