PHOG: Photometric and Geometric Functions for Textured Shape Retrieval

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dc.contributor.authorBiasotti, Silviaen_US
dc.contributor.authorCerri, Andreaen_US
dc.contributor.authorGiorgi, Danielaen_US
dc.contributor.authorSpagnuolo, Michaelaen_US
dc.contributor.editorYaron Lipman and Hao Zhangen_US
dc.date.accessioned2015-02-28T15:50:28Z
dc.date.available2015-02-28T15:50:28Z
dc.date.issued2013en_US
dc.description.abstractIn this paper we target the problem of textured 3D object retrieval. As a first contribution, we show how to include photometric information in the persistence homology setting, also proposing a novel theoretical result about multidimensional persistence spaces. As a second contribution, we introduce a generalization of the integral geodesic distance which fuses shape and color properties. Finally, we adopt a purely geometric description based on the selection of geometric functions that are mutually independent. The photometric, hybrid and geometric descriptions are combined into a signature, whose performance is tested on a benchmark dataset.en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/cgf.12168en_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.subject[Computer Graphics]en_US
dc.subjectShape analysis and synthesisen_US
dc.subject[Computer Graphics]en_US
dc.subjectGeometry and topology representationsen_US
dc.titlePHOG: Photometric and Geometric Functions for Textured Shape Retrievalen_US
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32-Issue 5
SGP13: Eurographics Symposium on Geometry Processing (CGF 32-5)