Papers for

cultural heritage software developers

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

Computer vision methods face challenges in art history research

Computer Vision Applications for Art History: Reflections and paradigms for future research

Abstract: One of the contributing factors to the continuing debate among art historians over the use of computational methods in art history research is that they do not consider the core of today's art history research questions. The lack of close collaboration between the two involved research communities makes the definition of contemporary art-historical methods as well-defined computer vision problems extremely difficult. For that purpose, it is devised as a methodology to study articles in art history journals from a computer science perspective. The objective is to identify which image features art historians utilise within their research and describe them in immediate and meaningful terms to the computer vision research community. Finally, some paradigms that could serve as a new starting point for exploring how computer vision applications for art history can address the core of today's art history research are given.

Mon 2 NovComputer Vision and Pattern RecognitionComputers and SocietyDigital Libraries

The gist

Art historians and computer scientists often struggle to work together because they focus on different research questions and methods. This paper looks at art history articles to find which visual features art historians use and tries to explain these in terms that computer vision can understand. The goal is to help future computer vision tools better address important questions in art history by bridging this gap. The authors also suggest new directions for collaborations to make these tools more relevant.

Open → 2611.02649v1