dc.contributor.author | Grabner, Harald | en_US |
dc.contributor.author | Ullrich, Torsten | en_US |
dc.contributor.author | Fellner, Dieter W. | en_US |
dc.contributor.editor | Reinhard Klein and Pedro Santos | en_US |
dc.date.accessioned | 2014-12-16T07:24:49Z | |
dc.date.available | 2014-12-16T07:24:49Z | |
dc.date.issued | 2014 | en_US |
dc.identifier.isbn | 978-3-905674-75-0 | en_US |
dc.identifier.uri | http://dx.doi.org/10.2312/gch.20141317 | en_US |
dc.description.abstract | In this paper we present a novel 3D model retrieval approach based on generative modeling techniques. In our approach generative models are created by domain experts in order to describe 3D model classes. These generative models span a shape space, of which a number of training samples is taken at random. The samples are used to train content-based retrieval methods. With a trained classifier, techniques based on semantic enrichment can be used to index a repository. Furthermore, as our method uses solely generative 3D models in the training phase, it eliminates the cold start problem. We demonstrate the effectiveness of our method by testing it against the Princeton shape benchmark. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.subject | H.3.3 [Computer Graphics] | en_US |
dc.subject | Information Systems | en_US |
dc.subject | Information Search and Retrieval | en_US |
dc.subject | I.2.4 [Computer Graphics] | en_US |
dc.subject | Knowledge Representation Formalisms and Methods | en_US |
dc.subject | Representations (procedural and rule | en_US |
dc.subject | based) | en_US |
dc.subject | I.4.8 [Computer Graphics] | en_US |
dc.subject | Scene Analysis | en_US |
dc.subject | Object recognition | en_US |
dc.title | Content-based Retrieval of 3D Models using Generative Modeling Techniques | en_US |
dc.description.seriesinformation | Eurographics Workshop on Graphics and Cultural Heritage - Short Papers / Posters | en_US |