Speakers
Description
Almost every art historian has heard of Iconclass. Less known is that the creator of Iconclass, Henri van de Waal (1910-1972) for the greater part of his life worked on another classification of the arts, with the title: “Beeldleer” (Iconology). It was intended as a tool for “iconological exploration” for mapping still uncharted territories of the arts. In line with Aby Warburg and his followers, Van de Waal rejected commonly rigid categorizations of art according to genres and periods and proposed instead new more associative and cross-cultural ways of arranging images blurring the boundaries between different disciplines such as art history, philosophy, and anthropology.
The claim is put forward that linking Van de Waal’s unfinished classification of the arts to Iconclass and potentially future ontologies in the domain of the digital humanities will enhance the quality of the classification of results in computer vision experimentation. The potential of Iconclass for describing such results of experiments foremost based on figurative Western art has already been outlined in digital art historical studies. In this paper the additional value of linking to Beeldleer (Iconology) for classifying cross-cultural, non-figurative and more syntactic aspects of the arts as well will be explored. Similar to the automated step by step approach of deep learning underlying computer vision to recognize features and patterns in data that are more meaningful than other, our human reading of the produced results is a gradual process of understanding images in the context of our knowledge. Therefore, we propose associative systems that allow for the pre-classification, classification and post-classification(contextualization) of images in order to compare, to benchmark and to contextualize (intermediate) results of computer vision in a meaningful way. A beta-version of such an associative system will be presented.