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Procedural generation of imaginative trees using a space colonization algorithm
Mälardalen University, School of Innovation, Design and Engineering.
2017 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The modeling of trees is challenging due to their complex branching structures. Three different ways to generate trees are using real world data for reconstruction, interactive modeling methods and modeling with procedural or rule-based systems. Procedural content generation is the idea of using algorithms to automate content creation processes, and it is useful in plant modeling since it can generate a wide variety of plants that can adapt and react to the environment and changing conditions. This thesis focuses on and extends a procedural tree generation technique that uses a space colonization algorithm to model the tree branches' competition for space, and shifts the previous works' focus from realism to fantasy. The technique satisfied the idea of using interaction between the tree's internal and external factors to determine its final shape, by letting the designer control the where and the how of the tree's growth process. The implementation resulted in a tree generation application where the user's imagination decides the limit of what can be produced, and if that limit is reached can the application be used to randomly generate a wide variety of trees and tree-like structures. A motivation for many researchers in the procedural content generation area is how it can be used to augment human imagination. The result of this thesis can be used for that, by stepping away from the restrictions of realism, and with ease let the user generate widely diverse trees, that are not necessarily realistic but, in most cases, adapts to the idea of a tree.

Place, publisher, year, edition, pages
2017. , p. 48
Keywords [en]
tree modeling, procedural content generation, space colonization algorithm, procedural modeling, tree generation
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-35577OAI: oai:DiVA.org:mdh-35577DiVA, id: diva2:1105996
Subject / course
Computer Science
Supervisors
Examiners
Available from: 2017-11-27 Created: 2017-06-06 Last updated: 2018-01-13Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • de-DE
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  • en-US
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  • nn-NB
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  • Other locale
More languages
Output format
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