Riedones3D:用于注册和细粒度聚类的凯尔特硬币数据集

Sofiane Horache, Jean-Emmanuel Deschaud, Franccois Goulette, K. Gruel, Thierry Lejars, O. Masson
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引用次数: 1

摘要

根据硬币的形状对硬币进行分类是钱币研究的一个重要组成部分,对于理解部落的经济史至关重要(尤其是在凯尔特文化中不存在文学作品的情况下)。这是一项非常艰巨的任务,需要大量的时间和专业知识。为了把成千上万的硬币聚在一起,自动方法变得很有必要。然而,用于硬币模具聚类评估的公开数据集太少了,尽管它们对新方法的发展非常重要。因此,我们提出了一个新的3D数据集,包含2070个硬币扫描。利用这个数据集,我们提出了两个基准,一个是点云配准基准,这对硬币骰子识别至关重要,另一个是硬币骰子聚类基准。我们展示了如何自动聚类硬币以帮助专家,并对这两个任务执行初步评估。基线和数据集的代码将在https://www.npm3d.fr/coins-riedones3d和https:// www.chronocarto.eu/spip.php?article84&lang=fr上公开。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Riedones3D: a celtic coin dataset for registration and fine-grained clustering
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.
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