Guest lecture: Computer vision in the study of art: New rigorous approaches to the analysis of paintings and drawings
Dr. David Stork from Ricoh Innovations and Standford University will give a guest lecture on Wednesday 29th of October at 14:15 in B222.
Abstract:
Rigorous computer vision algorithms have been used to shed light on a number of recent controversies in the study of art. For example, illumination estimation and shape-from-shading methods developed for robot vision and digital photograph forensics can reveal the accuracy and the working methods of masters such as Jan van Eyck and Caravaggio and the question of whether they secretly traced optically projected images. Sophisticated analysis of the lighting over different figures in a realist painting has shown that the figures were painted under different lighting conditions and hence "compositted" into the image. Computer wavelet analysis has been used for attribution of the contributors in Perugino's Holy Family and works of Vincent van Gogh. Computer methods can dewarp the images depicted in convex mirrors depicted in famous paintings such as Jan van Eyck's Arnolfini portrait to reveal new views into artists' studios and shed light on their working methods. New principled, rigorous methods for estimating perspective transformations outperform traditional and ad hoc methods and yield new insights into the working methods of Renaissance masters. Statistical analysis of the color and shape of brush strokes allow us to digitally "peel away" layers of brush strokes to reveal intermediate stages in the development of paintings, such as van Gogh's self portraits. Sophisticated computer graphics recreations of tableaus allow us to explore "what if" scenarios, and reveal the lighting and working methods of masters such as Caravaggio and Velązquez.
How do these computer methods work? What can computers reveal about images that even the best-trained connoisseurs, art historians and artist cannot? How much more powerful and revealing will these methods become? In short, how is the "hard humanities" field of computer image analysis of art changing our understanding of paintings and drawings?
This profusely illustrate lecture for scholars interested in computer vision, pattern recognition and image analysis will include works by Jackson Pollock, Vincent van Gogh, Jan van Eyck, Hans Memling, Lorenzo Lotto, and several others.
About the speaker:
Dr. David G. Stork is Chief Scientist of Ricoh Innovations and Consulting Professor of Statistics at Stanford University, where he has held appointments, taught, and sat on dissertation committees frequently over the last 20 years in the departments of Computer Science, Electrical Engineering, Statistics, Psychology and Art and Art History. He is a Fellow of the International Association for Pattern Recognition and founding general chairman of the Optical Society of America's Digital image processing and analysis conference (DIPA).