Dominant Texture and Diffusion Distance Manifolds

dc.contributor.authorLu, Jianyeen_US
dc.contributor.authorDorsey, Julieen_US
dc.contributor.authorRushmeier, Hollyen_US
dc.date.accessioned2015-02-23T10:17:33Z
dc.date.available2015-02-23T10:17:33Z
dc.date.issued2009en_US
dc.description.abstractTexture synthesis techniques require nearly uniform texture samples, however identifying suitable texture samples in an image requires significant data preprocessing. To eliminate this work, we introduce a fully automatic pipeline to detect dominant texture samples based on a manifold generated using the diffusion distance. We define the characteristics of dominant texture and three different types of outliers that allow us to efficiently identify dominant texture in feature space. We demonstrate how this method enables the analysis/synthesis of a wide range of natural textures. We compare textures synthesized from a sample image, with and without dominant texture detection. We also compare our approach to that of using a texture segmentation technique alone, and to using Euclidean, rather than diffusion, distances between texture features.en_US
dc.description.number2en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume28en_US
dc.identifier.doi10.1111/j.1467-8659.2009.01407.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.pages667-676en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2009.01407.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltden_US
dc.titleDominant Texture and Diffusion Distance Manifoldsen_US
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