Purpose

Based on the highlights of The Metropolitan Museum of Art's collection, the purpose of this paper is to examine the similarities and differences between the subject keywords tags assigned by the museum and those produced by three computer vision systems.

Design/methodology/approach

This paper uses computer vision tools to generate the data and the Getty Research Institute's Art and Architecture Thesaurus (AAT) to compare the subject keyword tags.

Findings

This paper finds that there are clear opportunities to use computer vision technologies to automatically generate tags that expand the terms used by the museum. This brings a new perspective to the collection that is different from the traditional art historical one. However, the study also surfaces challenges about the accuracy and lack of context within the computer vision results.

Practical implications

This finding has important implications on how these machine-generated tags complement the current taxonomies and vocabularies inputted in the collection database. In consequence, the museum needs to consider the selection process for choosing which computer vision system to apply to their collection. Furthermore, they also need to think critically about the kind of tags they wish to use, such as colors, materials or objects.

Originality/value

The study results add to the rapidly evolving field of computer vision within the art information context and provide recommendations of aspects to consider before selecting and implementing these technologies.

中文翻译：

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大都会艺术博物馆藏品的人工和机器生成标签的批判性比较分析

目的

基于大都会艺术博物馆馆藏的亮点，本文的目的是检验博物馆分配的主题关键词标签与三个计算机视觉系统生成的主题关键词标签之间的异同。

设计/方法/方法

本文使用计算机视觉工具生成数据和盖蒂研究所的艺术与建筑辞典（AAT）比较主题关键词标签。

发现

本文发现，使用计算机视觉技术自动生成标签以扩展博物馆使用的术语是有明显机会的。这为收藏带来了一种不同于传统艺术历史收藏的新视角。然而，该研究也对计算机视觉结果中的准确性和缺乏上下文提出了挑战。

实际影响

这一发现对这些机器生成的标签如何补充输入到集合数据库中的当前分类法和词汇表具有重要意义。因此，博物馆需要考虑选择过程，以选择将哪种计算机视觉系统应用于其收藏。此外，他们还需要批判性地思考他们希望使用的标签类型，例如颜色、材料或物体。

原创性/价值

研究结果增加了艺术信息背景下快速发展的计算机视觉领域，并提供了在选择和实施这些技术之前要考虑的方面的建议。