Conrad Rudolph

Inventing the Exegetical Stained-Glass Window: Suger, Hugh, and a New Elite Art

Abbot Sugers art program at St-Denis has long been credited with the reintroduction of “allegory” into Western art after centuries of disuse. A new understanding of that reintroduction is caught up in a web of previously unrecognized issues: that inventing the exegetical stained-glass window acted as a justification of the monastic use of art, that this claim was contradicted by new thought on art and the senses, that this new art appeared first not at St-Denis but elsewhere, and that the construction of a new elite art for the literate layperson emerged from all this.

In the Beginning: Theories and images of creation in Northern Europe in the twelfth century

The twelfth century witnessed a phenomenal explosion of interest in creation theory, an interest that was accompanied by an equally phenomenal increase in creation imagery of almost 900 per cent over the previous century. Often taken at face value by scholars as straightforward creation scenes or as the unique iconographical expressions of various patristic or contemporary writers on creation without reference to the larger, on-going dialectical struggles of which these writings and the artworks were a part, these images should instead be seen as active factors in the process of forming elite opinion as a prelude to conditioning public opinion on a broader, lower level.

Computerized Face Recognition in Renaissance Portrait Art: A quantitative measure for identifying uncertain subjects in ancient portraits

This article explores the feasibility of face-recognition technologies for analyzing works of portraiture and, in the process, provides a quantitative source of evidence to art historians in answering many of their ambiguities concerning identity of the subject in some portraits and in understanding artists? styles. Works of portrait art bear the mark of visual interpretation of the artist. Moreover, the number of samples available to model these effects is often limited. Based on an understanding of artistic conventions, we show how to learn and validate features that are robust in distinguishing subjects in portraits (sitters) and that are also capable of characterizing an individual artist?s style. This can be used to learn a feature space called portrait feature space (PFS) that is representative of quantitative measures of similarities between portrait pairs known to represent same/different sitters. Through statistical hypothesis tests, we analyze uncertain portraits against known identities and explain the significance of the results from an art historian?s perspective. Results are shown on our data consisting of over 270 portraits belonging largely to the Renaissance era.

Quantitative modeling of artist styles in Renaissance face portraiture

Renaissance portraits were depictions of some important royals of those times. Analysis of faces in these portraits can provide valuable dynastical information in addition to enriching personal details of the depicted sitter. Such studies can offer insights to the art-history community in understanding and linking personal histories. In particular, face recognition technologies can be useful for identifying subjects when there is ambiguity. However, portraits are subject to several complexities such as aesthetic sensibilities of the artist or social standing of the sitter. Thus, for robust automated face recognition, it becomes important to model the characteristics of the artist. In this paper, we focus on modeling the styles of artists by considering case studies involving Renaissance art-works. After a careful examination of artistic trends, we arrive at relevant features for analysis. From a set of instances known to match/not match, we learn distributions of match and non-match scores which we collectively refer to as the portrait feature space (PFS). Thereafter, using statistical permutation tests we learn which of the chosen features were emphasized in various works involving (a) same artist depicting same sitter, (b) same sitter but by different artists and (c) same artist but depicting different sitters. Finally, we show that the knowledge of these specific choices can provide valuable information regarding the sitter and/or artist.