Re-Presentations of Art Collections

Abstract

The objective of this paper is to show how modern computer vision methods can be used to aid the art or book historian in analysing large digital art collections. We make three contributions: first, we show that simple document processing methods in combination with accurate instance based retrieval methods can be used to automatically obtain all the illustrations from a collection of illustrated documents. Second, we show that image level descriptors can be used to automatically cluster collections of images based on their categories, and thereby represent a collection by its semantic content. Third, we show that instance matching can be used to identify illustrations from the same source, e.g. printed from the same woodblock, and thereby represent a collection in a manner suitable for temporal analysis of the printing process. These contributions are demonstrated on a collection of illustrated English Ballad sheets.