Quantitative Analysis of Objects in Prisoner Artworks

TL;DR

This paper presents a comprehensive quantitative analysis of nearly two thousand Holocaust prisoner artworks using object detection and an interactive dashboard, enhancing understanding and engagement with these historical visual testimonies.

Contribution

It introduces a novel dataset and applies machine learning techniques to analyze prisoner artworks, along with developing an interactive tool for deeper exploration.

Findings

The object detection framework identified 19,377 objects in the artworks.

The dashboard received positive feedback from domain experts for its usability.

The project demonstrates digital methods' value in Holocaust remembrance and education.

Abstract

Prisoners of Nazi concentration camps created paintings as a means to express their daily life experiences and feelings. Several thousand such paintings exist, but a quantitative analysis of them has not been carried out. We created an extensive dataset of 1,939 Holocaust prisoner artworks, and we employed an object detection framework that found 19,377 objects within these artworks. To support the quantitative and qualitative analysis of the art collection and its objects, we have developed an intuitive and interactive dashboard to promote a deeper engagement with these visual testimonies. The dashboard features various visual interfaces, e.g., a word cloud showing the detected objects and a map of artwork origins, and options for filtering. We presented the interface to domain experts, whose feedback highlights the dashboard's intuitiveness and potential for both quantitative and qualitative analysis while also providing relevant suggestions for improvement. Our project demonstrates the benefit of digital methods such as machine learning and visual analytics for Holocaust remembrance and educational purposes.