Visualization and Extraction of Carvings for Heritage Conservation

A language to analyze, describe, and explore collections of visual art

A vast quantity of art in existence today is inaccessible to individuals. If people want to know the different types of art that exist, how individual works are connected, and how works of art are interpreted and discussed in the context of other works, they must utilize means other than simply viewing the art. Therefore, this paper proposes a language to analyze, describe, and explore collections of visual art (LadeCA). LadeCA combines human interpretation and automatic analyses of images, allowing users to assess collections of visual art without viewing every image in them. This paper focuses on the lexical base of LadeCA. It also outlines how collections of visual art can be analyzed, described, and explored using a LadeCA vocabulary. Additionally, the relationship between LadeCA and indexing systems, such as ICONCLASS or AAT, is demonstrated, and ways in which LadeCA and indexing systems can complement each other are highlighted.

VeCHArt: Visually Enhanced Comparison of Historic Art Using an Automated Line-Based Synchronization Technique

The analysis of subtle deviations between different versions of historical prints has been a long-standing challenge in art history research. So far, this challenge has required extensive domain knowledge, fine-tuned expert perception, and time-consuming manual labor. In this paper we introduce an explorative visual approach to facilitate fast and accurate support for the task of comparing differences between prints such as engravings and woodcuts. To this end, we have developed a customized algorithm that detects similar stroke-patterns in prints and matches them in order to allow visual alignment and automated deviation highlighting. Our visual analytics system enables art history researchers to quickly detect, document, and categorize qualitative and quantitative discrepancies, and to analyze these discrepancies using comprehensive interactions. To evaluate our approach, we conducted a user study involving both experts on historical prints and laypeople. Using our new interactive technique, our subjects found about 20 percent more differences compared to regular image viewing software as well as "paper-based" comparison. Moreover, the laypeople found the same differences as the experts when they used our system, which was not the case for conventional methods. Informal feedback showed that both laypeople and experts strongly preferred employing our system to working with conventional methods.