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dc.contributor.authorSchinko, Christoph
dc.date.accessioned2023-05-10T11:17:16Z
dc.date.available2023-05-10T11:17:16Z
dc.date.issued2018
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/2633331
dc.description.abstractThe thesis "Shape Processing for Content Generation" by Christoph Schinko presents work on generative modeling, novel applications for inverse generative modeling, and visualization systems. These areas are regarded as steps in the context of shape processing, hence the thesis is structured that way. After defining the term shape, the first part of the thesis is concerned with shape descriptions. While some shape descriptions are of abstract nature, others can be directly used, for example, in the field of computer aided geometric design. The process of working with shape descriptions is called shape modeling. This topic includes primitive modeling using 3D modeling software or scene description languages, semantic modeling dealing with meta data, and generative modeling using domain specific information. An application for generative modeling in the context of wedding rings is implemented using a domain specific language for generative modeling { the Generative Modeling Language (GML). The multitude of involved platforms (the GML is implemented in C++, the postfix notation of the language itself is similar to Adobe Postscript, the application is targeted for the web) has inspired the idea to create an innovative meta-modeler approach called "Euclides". Its innovative concept of using a beginner-friendly syntax in combination with translation back-ends for various different platforms presents a foundation for the platform-independent creation of generative building blocks. This approach significantly reduces the effort for implementing and maintaining generative description for different platforms. Building up on previous work on finding the best generative description of one or several given instances of an object class, an application to analyze digitized objects in terms of changes and damages is presented. The system automatically combines generative descriptions with reconstructed objects and performs a nominal/actual value comparison. By applying the variances of the reconstructed objects to a different parameter set of the generative description, new shapes can be created. With this novel approach, the design of shapes using both low-level details and high-level shape parameters is possible. The last step in the context of shape processing is concerned with visualization systems for humans to perceive and interact with shapes. In this context, a novel method to project a coherent, seamless and perspectively corrected image from one particular viewpoint using an arbitrary number of projectors is presented. The approach distinguishes itself by being quick and efficient. The last contribution to this topic is describing an optimized stereoscopic display based on parallax barriers for a driving simulator.en_US
dc.language.isoenen_US
dc.titleShape Processing for Content Generationen_US
dc.typeThesisen_US


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