# Description and Retrieval of Geometric Patterns on Surface Meshes using an edge-based LBP approach

arXiv: https://arxiv.org/abs/1805.00719 · HTML: https://mlsanity.com/paper/1805.00719/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 May 2018.

## Built on by (most cited first, 1 of 1)

- [3D-TexSeg: Unsupervised Segmentation of 3D Texture using Mutual Transformer Learning](https://mlsanity.com/paper/2311.10651/) (2023)

## Abstract (arXiv)

While texture analysis is largely addressed for images, the comparison of the geometric reliefs on surfaces embedded in the 3D space is still an open challenge. Starting from the Local Binary Pattern (LBP) description originally defined for images, we introduce the edge-Local Binary Pattern (edgeLBP) as a local description able to capture the evolution of repeated, geometric patterns on surface meshes. Our extension is independent of the surface representation, indeed the edgeLBP is able to deal with surface tessellations characterized by non-uniform vertex distributions and different types of faces, such as triangles, quadrangles and, in general, convex polygons. Besides the desirable robustness properties the edgeLBP exhibits over a number of examples, we show how this description performs well for 3D pattern retrieval and compare our performances with the participants to a recent 3D pattern retrieval and classification contest.