Performing image-like convolution on triangular meshes

Claudio Tortorici, Naoufel Werghi, Stefano Berretti

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


Image convolution with a filtering mask is at the base of several image analysis operations. This is motivated by Mathematical foundations and by the straightforward way the discrete convolution can be computed on a grid-like domain. Extending the convolution operation to the mesh manifold support is a challenging task due to the irregular structure of the mesh connections. In this paper, we propose a computational framework that allows convolutional operations on the mesh. This relies on the idea of ordering the facets of the mesh so that a shift-like operation can be derived. Experiments have been performed with several filter masks (Sobel, Gabor, etc.) showing state-of-the-art results in 3D relief patterns retrieval on the SHREC'17 dataset. We also provide evidence that the proposed framework can enable convolution and pooling-like operations as can be needed for extending Convolutional Neural Networks to 3D meshes.

Original languageBritish English
Title of host publicationEG 3DOR 2018 - Eurographics Workshop on 3D Object Retrieval
Number of pages4
ISBN (Electronic)9783038680536
StatePublished - 2018
Event11th Eurographics Workshop on 3D Object Retrieval, 3DOR 2018 - Delft, Netherlands
Duration: 16 Apr 2018 → …

Publication series

NameEurographics Workshop on 3D Object Retrieval, EG 3DOR
ISSN (Print)1997-0463
ISSN (Electronic)1997-0471


Conference11th Eurographics Workshop on 3D Object Retrieval, 3DOR 2018
Period16/04/18 → …


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