Riedones3D: a celtic coin dataset for registration and fine-grained clustering

TL;DR

This paper introduces Riedones3D, a new 3D coin dataset and benchmarks for registration and clustering, aiming to automate and improve numismatic research on Celtic coins.

Contribution

It provides a novel public dataset of 2,070 coin scans and establishes benchmarks for point cloud registration and coin die clustering tasks.

Findings

Automatic clustering assists experts in numismatic research.

Preliminary evaluation demonstrates the dataset's utility for registration and clustering.

Baseline methods show promising results on the new benchmarks.

Abstract

Clustering coins with respect to their die is an important component of numismatic research and crucial for understanding the economic history of tribes (especially when literary production does not exist, in celtic culture). It is a very hard task that requires a lot of times and expertise. To cluster thousands of coins, automatic methods are becoming necessary. Nevertheless, public datasets for coin die clustering evaluation are too rare, though they are very important for the development of new methods. Therefore, we propose a new 3D dataset of 2 070 scans of coins. With this dataset, we propose two benchmarks, one for point cloud registration, essential for coin die recognition, and a benchmark of coin die clustering. We show how we automatically cluster coins to help experts, and perform a preliminary evaluation for these two tasks. The code of the baseline and the dataset will be publicly available at https://www.npm3d.fr/coins-riedones3d and https://www.chronocarto.eu/spip.php?article84&lang=fr