Recent museum exhibitions are becoming a means by which to satisfy visitor demands. In order to provide visitor-centric exhibitions, artwork must be analyzed based on the behavior of visitors, and not merely according to museum professionals' points of view. This study aims to analyze the relationship between museum visitors and artwork via a network analysis based on visitor behavior using object detection techniques. Cameras installed in a museum recorded visitors, and an object detector with a content-based image-retrieval technique tracked visitors from the videos. The durations spent with different artworks were measured, and the data was converted into a bipartite graph. The relationships between different artwork types were analyzed with a visitor-centered artwork network. Based on the visitors’ behavior, significant artworks were identified and the artwork network was compared to the arrangement of the museum. The tendency of edges in the artwork network was also examined considering visitors' preferences for artworks. The method used here makes it possible to collect quantitative data, with the results possibly used as a basis and for reference when analyzing artwork in a visitor-centered approach.

最近的博物馆展览正成为满足游客需求的一种手段。为了提供以游客为中心的展览，必须根据游客的行为来分析艺术品，而不仅仅是根据博物馆专业人员的观点进行分析。这项研究旨在通过使用对象检测技术基于访问者行为的网络分析来分析博物馆访问者与艺术品之间的关系。博物馆中安装的摄像机记录了访客，而采用基于内容的图像检索技术的物体检测器从视频中追踪了访客。测量在不同艺术品上花费的时间，并将数据转换为二分图。使用以游客为中心的艺术品网络分析了不同艺术品类型之间的关系。根据访问者的行为，确定了重要的艺术品，并将艺术品网络与博物馆的布置进行了比较。考虑到访客对艺术品的偏爱，还检查了艺术品网络中边缘的趋势。此处使用的方法使收集定量数据成为可能，并且在以游客为中心的方式分析艺术品时，可能将结果用作基础和参考。