dc.contributor.author | Nicolet, Baptiste | en_US |
dc.contributor.author | Ecormier-Nocca, Pierre | en_US |
dc.contributor.author | Memari, Pooran | en_US |
dc.contributor.author | Cani, Marie-Paule | en_US |
dc.contributor.editor | Wilkie, Alexander and Banterle, Francesco | en_US |
dc.date.accessioned | 2020-05-24T13:43:15Z | |
dc.date.available | 2020-05-24T13:43:15Z | |
dc.date.issued | 2020 | |
dc.identifier.isbn | 978-3-03868-101-4 | |
dc.identifier.issn | 1017-4656 | |
dc.identifier.uri | https://doi.org/10.2312/egs.20201025 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/egs20201025 | |
dc.description.abstract | Pair Correlation Functions (PCF) have been recently spreading as a reliable representation for distributions, enabling the efficient synthesis of point-sets, vector textures and object placement from examples. In this work we introduce a triangulationbased local filtering method to extend PCF-based analysis to exemplars with free-form boundaries. This makes PCF applicable to new problems such as the inpainting of missing parts in an input distribution, or the decomposition of complex, non-homogeneous distributions into a set of coherent classes, in which each category of points can be studied together with their intra and inter-class correlations. | en_US |
dc.publisher | The Eurographics Association | en_US |
dc.rights | Attribution 4.0 International License | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | ] |
dc.subject | I.3.5 [Computer Graphics] | |
dc.subject | Computational Geometry and Object Modeling | |
dc.subject | Boundary representations | |
dc.title | Pair Correlation Functions with Free-Form Boundaries for Distribution Inpainting and Decomposition | en_US |
dc.description.seriesinformation | Eurographics 2020 - Short Papers | |
dc.description.sectionheaders | Visualisation / NPR | |
dc.identifier.doi | 10.2312/egs.20201025 | |
dc.identifier.pages | 89-92 | |