Riedones3D：用于注册和细粒度聚类的凯尔特币数据集
Riedones3D: a celtic coin dataset for registration and fine-grained clustering
摘要：
将硬币按照模具进行分类是钱币学研究的重要组成部分，对于了解部落的经济史也至关重要（特别是在凯尔特文化中不存在文学作品的时候）。这是一项非常艰巨的任务，需要大量的时间和专业知识。为了集群成千上万的硬币，自动方法变得必要。然而，用于硬币模具聚类评估的公共数据集太少，尽管它们对于新方法的开发非常重要。因此，我们提出了一个新的3D数据集的2070扫描硬币。有了这个数据集，我们提出了两个基准，一个是点云注册，硬币模具识别必不可少的，和硬币模具聚类的基准。我们展示了如何自动聚类硬币来帮助专家，并对这两项任务进行了初步评估。基线代码和数据集将在https://www.npm3d.fr/coins-riedones3d和https://www.chronocarto.eu/spip.php?上公开提供article84&lang=fr
英文摘要：
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
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
