Computer Image Analysis in the Study of Art

Dr David G. Stork
Ricoh Innovations
Stanford University

Friday, Nov 20, 11am
SITE 5084, 800 King Edward Ave

Sponsored  by

Miri Research Lab


New computer methods have been used to shed light on a number of recent controversies in the study of art. For example, computer fractal analysis has been used in authentication studies of paintings attributed to Jackson Pollock recently discovered by Alex Matter. Computer wavelet analysis has been used for attribution of the contributors in Perugino's Holy Family. An international group of computer and image scientists is studying the brushstrokes in paintings by van Gogh for detecting forgeries. Sophisticated computer analysis of perspective, shading, color and form has shed light on David Hockney's bold claim that as early as 1420, Renaissance artists employed optical devices such as concave mirrors to project images onto their canvases. 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 computer image analysis changing our understanding of art? This profusely illustrate lecture for non-scientists will include works by Jackson Pollock, Vincent van Gogh, Jan van Eyck, Hans Memling, Lorenzo Lotto, and others. You may never see paintings the same way again.

Biography of David G. Stork

Dr. David G. Stork is Chief Scientist of Ricoh Innovations and has held academic appointments and taught in five departments at Stanford University over the last 20 years. The breadth of his interests and contriburtions is revealed through the academic departments and programs in which he has held faculty positions in leading liberal arts colleges and research universities: Physics, Mathematics, Electrical Engineering, Statistics, Computer Science, Neuroscience, Psychology, and Art and Art History. He is a Fellow of the International Association for Pattern Recognition, "For contributions to pattern recognition education, machine learning, speech recognition, and the application of computer vision to the study of art" and Chair of its Technical Committee on Computer Vision in Cultural Heritage Applications. He has published six books/proceedings volumes and has another in production, including Seeing the Light: Optics in nature, photography, color, vision and holography (Wiley), the leading textbook on optics in the arts, Computer image analysis in the study of art (SPIE), the first volume in this discipline, Computer vision and image analysis in the study of art (forthcoming), Pattern Classification (2nd ed., Wiley), the world's all-time best-selling textbook in the field, translated into three languages and used in courses in over 250 universites worldwide, and HAL's Legacy: 2001's computer as dream and reality (MIT), the source of his PBS television documentary 2001: HAL's Legacy. A graduate in physics of the Massachusetts Institute of Technology and the University of Maryland at College Park, he also studied art history at Wellesley College and was Artist-in-Residence through the New York State Council of the Arts. He holds 38 US patents and has published numerous technical papers on human and machine learning and perception of patterns, physiological optics, image understanding, concurrency theory, theoretical mechanics, optics, image processing. He has served on the editorial boards of five international journals and has delivered over 58 plenary, invited or distinguished lectures at universities and conferences (atop over 230 traditional invited colloquia and seminars).


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