Sunday 26 January • 8:00 – 12:15
Length: 4 hours
Level: Intermediate
Instructor:  David G. Stork

Learning Outcomes
This course will enable the attendee to:

• Identifying problems in the history and interpretation of fine art that are amenable to computer methods 
• Perspective analysis
• Brush stroke analysis
• Color analysis
• Lighting analysis
• Stylometry (quantification of artistic style) and artistic influence 
• Basics of art authentication

This course presents the application of rigorous image processing, computer vision, machine learning, computer graphics, and artificial intelligence techniques to problems in the history and interpretation of fine art paintings, drawings, murals, and other two-dimensional works, including abstract art.  The course focuses on the aspects of these problems that are unlike those addressed widely elsewhere in computer image analysis applied to physics-constrained images in photographs, videos, and medical images, such as the analysis of brushstrokes and marks, medium, inferring artists' working methods, compositional principles, stylometry (quantification of style), the tracing of artistic influence, and art attribution and authentication.  The course revisits classic problems, such as image-based object recognition, but in highly non-realistic, stylized artworks.  

Intended Audience
Students and scholars in imaging, image science, computer vision, and art and art history.

David G. Stork is widely considered a pioneer in the application of rigorous computer vision and image analysis to the study of fine art.  He is a graduate from MIT and the University of Maryland in physics, and has held faculty positions in physics, mathematics, electrical engineering, computer science, statistics, neuroscience, psychology, and art and art history variously at Wellesley and Swarthmore Colleges, and Clark, Boston and Stanford Universities.  He is a fellow of six international societies, and founding co-chair of "Electronic Imaging" Computer vision and image analysis of art symposium.  His 56 patents, more than 200 scholarly works, including eight books, have garnered over 75,000 citations.  He is completing "Pixels and paintings:  Foundations of computer-assisted connoisseurship" for Wiley Publishers.