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

TL;DR

This paper introduces edgeLBP, a novel local descriptor for surface meshes that captures geometric patterns and is robust to different tessellations, improving 3D pattern retrieval and classification.

Contribution

The paper presents edgeLBP, an extension of LBP for 3D surface meshes, capable of handling various tessellations and improving geometric pattern analysis.

Findings

edgeLBP effectively captures geometric patterns on surface meshes.

The method outperforms existing approaches in 3D pattern retrieval.

edgeLBP demonstrates robustness across different mesh tessellations.

Abstract

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.