dc.contributor.author | Giachetti, Andrea | en_US |
dc.contributor.editor | Ju, Tao and Vaxman, Amir | en_US |
dc.date.accessioned | 2018-07-27T12:54:35Z | |
dc.date.available | 2018-07-27T12:54:35Z | |
dc.date.issued | 2018 | |
dc.identifier.issn | 1467-8659 | |
dc.identifier.uri | https://doi.org/10.1111/cgf.13493 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.1111/cgf13493 | |
dc.description.abstract | In 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.publisher | The Eurographics Association and John Wiley & Sons Ltd. | en_US |
dc.subject | I.3.5 [Computer Graphics] | |
dc.subject | Computational Geometry and Object Modeling | |
dc.subject | Curve | |
dc.subject | surface | |
dc.subject | solid | |
dc.subject | and object representations | |
dc.title | Effective Characterization of Relief Patterns | en_US |
dc.description.seriesinformation | Computer Graphics Forum | |
dc.description.sectionheaders | Shape Analysis and Representation | |
dc.description.volume | 37 | |
dc.description.number | 5 | |
dc.identifier.doi | 10.1111/cgf.13493 | |
dc.identifier.pages | 83-92 | |