Effective Characterization of Relief Patterns

Simple item page
dc.contributor.authorGiachetti, Andreaen_US
dc.contributor.editorJu, Tao and Vaxman, Amiren_US
dc.date.accessioned2018-07-27T12:54:35Z
dc.date.available2018-07-27T12:54:35Z
dc.date.issued2018
dc.description.abstractIn this paper, we address the problem of characterizing relief patterns over surface meshes independently on the underlying shape. We propose to tackle the problem by estimating local invariant features and encoding them using the Improved Fisher Vector technique, testing both features estimated on 3D meshes and local descriptors estimated on raster images created by encoding local surface properties (e.g. mean curvature) over a surface parametrization. We compare the robustness of the obtained descriptors against noise and surface bending and evaluate retrieval performances on a specific benchmark proposed in a track of the Eurographics Shape REtrieval Contest 2017. Results show that, with the proposed framework, it is possible to obtain retrieval results largely improving the state of the art and that the image-based approach is still effective when the underlying surface is heavily deformed.en_US
dc.description.number5
dc.description.sectionheadersShape Analysis and Representation
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume37
dc.identifier.doi10.1111/cgf.13493
dc.identifier.issn1467-8659
dc.identifier.pages83-92
dc.identifier.urihttps://doi.org/10.1111/cgf.13493
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf13493
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectI.3.5 [Computer Graphics]
dc.subjectComputational Geometry and Object Modeling
dc.subjectCurve
dc.subjectsurface
dc.subjectsolid
dc.subjectand object representations
dc.titleEffective Characterization of Relief Patternsen_US
Files
Collections
37-Issue 5