Image is Everything

Emily L. Spratt has given us an account of an important encounter. One in which a computer scientist approaches an art historian with a question. This leads to a survey of computer scientists and art historians that shows deep pride that runs through both disciplines. Pride that offers questions about disciplinary positions and roles. In “Toward automated discovery of artistic influence,” a team of computer scientists from Rutgers outline their endeavor to explore a deeply humanities-founded issue of understanding artistic influence in art. “Re-presentations of Art Collections” is written by engineers, a literary scholar, and a librarian. “Multi-Feature Matching of Fresco Fragments” is an intersection point for an interdisciplinary multi-university attempt to approach an art history problem using high-level computational methods.

Dealing with computational problems that arise out of working with images is at the core of my scholarship. Throughout this weeks readings, we encountered practitioners of computer science, art history, english language and literature, library science, and engineering who are grappling with interdisciplinary problems with interdisciplinary answers. These are problems that illustrate a necessity for humanities, social science, and science scholars to work on interdisciplinary ground. Our class is founded on the notion that we need to be able to collaborate on professional terms.

There is no question that each discipline in the university holds it’s own questions, techniques, approaches, and canon. Digital Humanities is not a replacement for traditional disciplines, but rather, DH seeks to create scholarship that is grounded in conversation and collaboration. We are losing significant amounts of time because of hard stances on what the institution, what the disciplines, should be studying. Who is superior in a collaborative relationship is an unnecessary and unproductive discussion topic.

Spratt identifies “three main issues that demand further attention: the use of language between fields to describe concepts; the problem in the lack of uniformity in the interpretation of art; and the separate trajectories within computer science and art history regarding aesthetic interpretation” (15). All of these issues are conversations that we have encountered in our class discussions. There has yet to be answers established for any of them. Further, Spratt’s claim that “future entanglement between computer science and art history is promising” (18) is a valuable assessment that should be cited in our continued discussion.

We are seeing promising ground that can be tread, but we still aren’t there yet.

At the start of this class I had a clear idea of how my research could be furthered in talking with computer scientists about computational problems of interest to multiple disciplines. At this stage, weeks in, I am more concerned with developing a strategy for dialogue between the disciplines.

  1. Saleh et al, “Toward automated discovery of artistic influence,”Multimedia Tools and Applications, Augsut 2014.
  2. Emily L. Spratt and Ahmed Elgammal, “The Digital Humanities Unveiled: Perceptions Held by Art Historians and Computer Scientists about Computer Vision Technology ,” self-published. Also, review the survey results on the project’s home page.
  3. Chung et al, “Re-presentations of Art Collections,” presented at VisArt 2014 Workshop, “When Computer Vision Meets Art,” held in conjunction with ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6, 2014
  4. Toler-Franklin et al, “Multi-feature matching of fresco fragments,” ACM Transactions on Graphics (TOG) 29(6), December 2010.