Now that the unanimous independent review in the scholarly literature and of a four-day symposium devoted to testing Hockney's tracing theory for the early Renaissance (1430–1550)—from scientists, historians of art and optics, and a curator—have rejected the claims (or at best found the claims unproven), that every challenge to the data and methods of several rebutters have been rejected by independent experts from several institutions, that no scholarly papers have questioned these rebuttals, and that Mr. Hockney himself seems to have abandoned the tracing theory (feeling that early Renaissance artists merely saw and were influenced by projected images), after eight years it is time to move on to more productive areas of computer vision in the visual arts. Nevertheless, readers interested in the tracing theory can read more here.

Presentation videos (click on the first slide, wait one minute to load, then click on each slide to advance)

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Technical publications

David G. Stork, "Color and illumination in the Hockney theory: A critical evaluation," Proceedings of the Color Imaging Conference (CIC11), Scottsdale AZ, pp. 11–15, November 2003
Shows that Hockney's projection method does not significantly aid in the rendering of color and shading in paintings, key properties of the "opticality" that motivated the theory; shows that direct solar illumination is required, which is implausible for many works in the debate. (pdf)
David G. Stork, "Were optical projections used in early Renaissance painting? A geometric vision analysis of Jan van Eyck's Arnolfini portrait and Robert Campin's Mérode Altarpiece," SPIE Electronic Imaging, Vision geometry XII, Longin J. Latecki, David M. Mount and Angela Y. Wu (eds.), pp. 23–30, 2004
Rebuts Hockney and Falco's suggestion that the concave mirror in the Arnolfini portrait could be turned around and used for projection in the Arnolfini portrait; rebuts their claim that the chandelier "is in perfect perspective" and thus consistent with a projection; gives a more plausible non-optical explanation of the "break" in the trellis in the right-hand panel of the Mérode Altarpiece. (pdf)
David G. Stork, "Did Jan van Eyck build the first 'photocopier' in 1432?" SPIE Electronic imaging color imaging IX: Processing, hardcopy, and applications, vol. 5293, Reiner Eschbach and Gabriel G. Marcu (eds.), pp. 50–56, 2004
Presents several alternate non-optical explanations for the visual features in the Albergati portrait, and points to physical evidence supporting mechanical (not optical) copying and enlarging by compasso da reduzione or Reductionszirkel, evidence that plays no role whatsoever in the optical projection explanation. (pdf)
David G. Stork, "Optics and the Old Masters Revisited," Optics and Photonics News 15(3): 30–37, March 2004
A popular presentation of the rebuttals to Hockney's theory concerning van Eyck's Arnolfini portrait. (pdf)
David G. Stork, "Did Hans Memling employ optical projections when painting Flower still-life?" Leonardo 38(2): 57–62, 2005
Shows that the perspective evidence in Flower still-life supports the claim that both the front and the back of the carpet are not in proper perspective is more salient than the evidence that is, at best, consistent with the use of optics, thereby rebutting Hockney and Falco's claim this painting was created using projections. (pdf)
Antonio Criminisi and David G. Stork, "Did the great masters use optical projections while painting? Perspective comparison of paintings and photographs of Renaissance chandeliers," in Josef Kittler, Maria Petrou and Mark S. Nixon (eds.), Proceedings of the 17th International Conference on Pattern Recognition, Volume IV, pp. 645–648, 2004
A rigorous demonstration that the perspective in the Arnolfini chandelier is not "in perfect perspective," thereby undercutting Hockney's claim it was painted using projections; shows that the physical chandelier would have to have been implausibly deformed compared to surviving chandeliers to be even consistent with the projection claims; shows that talented realist artists can paint a complex chandelier "by eye" in better perspective than the Arnolfini chandelier. (pdf)
David G. Stork, "Did Georges de la Tour use optical projections while painting Christ in the carpenter's studio?" SPIE Electronic Imaging: Image and video communications and processing vol. 5685, Amir Said and John G. Apostolopoulos (eds.), pp. 214–219, 2005
Uses cast-shadow analysis to rebut Hockney's claim that de la Tour used bright illumination from "outside the frame" or "in place of the other figure" and optical projections when painting his "nocturne" works. (pdf)
David G. Stork, "Did early Renaissance painters trace optical projections? Evidence pro and con," SPIE Electronic imaging, Vision geometry XIII, vol. 5675, Longin J. Latecki, David M. Mount and Angela Y. Wu (eds.), pp. 25–31, 2005
An overview of the case for and against Hockney's theory.(pdf)
David G. Stork, "Asymmetry in 'Lotto carpets' and implications for Hockney's optical projection theory," SPIE Electronic imaging: Human vision and electronic imaging X, vol. 5666, Bernice E. Rogowitz, Thrasyvoulos N. Pappas and Scott J. Daly (eds.), pp. 337–343, 2005
Shows that the key assumption of Hockney and Falco—that the physical carpet was symmetric—is likely false; explains perspective anomalies as precisely as the optical theory but without requiring complex and undocumented optics. (pdf)
Christopher W. Tyler and David G. Stork, "Did Lorenzo Lotto use optical projections when painting Husband and wife?," Optical Society of America Annual Meeting, 2004 (abstract)
Describes the asymmetry in "Lotto carpets" surviving in museum collections (rejecting Hockney and Falco's key assumption that it was symmetric); provides several non-optical explanations for the "blur" in the painting. (pdf)
Thomas Ketelsen, Olaf Simon, Ina Reiche, Silke Merchel, and David G. Stork, "Evidence for mechanical (not optical) copying and enlarging in Jan van Eyck's Portrait of Niccolò Albergati," Optical Society of America Annual Meeting, 2004 (abstract)
Describes pinprick holes discovered in the Albergati silverpoint consistent with the use of a mechanical device such as a Reductionszirkel, but not with the use of optics; describes how the visual evidence in the works is more consistent with mechanical rather than optical copying/enlarging; describes experimental "re-enactment" of the copying by Reductionszirkel. (pdf)
David G. Stork, "Optics and realism in Renaissance art," Scientific American 291(6):76–84, December 2004
A popular presentation of rebuttals to Hockney and Falco on two key works of Jan van Eyck.(pdf)
David G. Stork, "Spieglein, Spieglein an der Wand" (in German), pp. 58–61, in a special edition of Spektrum der Wissenschaft on Forschung und Technik in der Renaissance, 2004
An abridged German translation of the Scientific American article. (pdf)
David G. Stork, "Optique et réalisme dans l'art de la Renaissance" (in French), Revue Pour la Science 327, pp. 74–86, French edition of Scientific American, January 2005
An abridged French translation of the Scientific American article. (pdf)
David G. Stork, "Tracing the history of art," review of Early science and medicine: Optics, instruments and painting, 1420-1720: Reflections on the Hockney-Falco theory, edited by Sven Dupré, Nature 438(7070): 916–917, December 15, 2005
A review of the proceedings of a four-day workshop devoted to exploring Hockney's theory. (pdf)
David G. Stork and M. Kimo Johnson, "Estimating the location of illuminants in realist master paintings: Computer image analysis addresses a debate in art history of the Baroque," Proceedings of the 18th International Conference on Pattern Recognition, Volume I, pp. 255–258, 2006
The first application of the occluding-contour algorithm to the problem of inferring the direction of illumination in realist paintings. Reconfirms the shadow analysis and scholarly consensus that the illumination in Georges de la Tour's Christ in the carpenter's studio is the candle, rebutting Hockney's claim that the painting was executed using an optical projector. (pdf)
David G. Stork, "Mathematical foundations for quantifying shape, shading and cast shadows in realist master drawings and paintings," SPIE Mathematics of data/image pattern recognition, compression and encryption with applications IX, Gerhard X. Ritter, Mark S. Schmalz, Junior Barrera and Jaakko T. Astola (eds.), volume 6314, pp. 63150K1–K6, 2006
The Bayesian statistical method for integrating various classes of information about the illumination in images including realist paintings such as the works of Caravaggio and Georges de la Tour. (pdf)
David G. Stork, "Computer vision, image analysis and master art, Part I," IEEE Multimedia 13(3): 16–20 (July-September 2006)
An invited tutorial on rigorous analysis of perspective in paintings; shows perspective of a painting of a chandelier done entirely by eye is superior to that of the Arnolfini chandelier, thereby rebutting the claim of Hockney and Falco that the Arnolfini chandelier was painted using optical projections. (pdf)
David G. Stork and M. Kimo Johnson, "Computer vision, image analysis and master art, Part II," IEEE Multimedia 13(4): 12–17 (October-December, 2006)
An invited tutorial on finding the illuminant in realist paintings, such as works of Georges de la Tour. Shows that the image evidence overwhelming refutes Hockney's unorthodox claim that Christ in the carpenter's studio was painted with the light source in place of the figures rather than, say, the location of the candle. (pdf)
David G. Stork and Marco Duarte, "Computer vision, image analysis and master art, Part III," IEEE Multimedia 14(1): 14–18 (January-March, 2007)
An invited tutorial on Chamfer distance and other methods of quantifying form, as in drawings, with application to Jan van Eyck's Albergati portrait. (pdf)
David G. Stork and Marco Duarte, "Fidelity analysis of mechanically aided copying/enlarging of Jan van Eyck's Portrait of Niccolò Albergati," SPIE Electronic imaging: Vision geometry XV, vol. 6499, Longin Jan Latecki, David M. Mount and Angela Y. Wu (eds.), pp. 649903-1 to 649903-6 (2007)
Shows that a talented realist artist using mechanical (not optical) methods from the 15th century can copy Jan van Eyck's Albergati portrait with a fidelity roughly the same as van Eyck. (pdf)
David G. Stork, "Aberration analysis of the putative projector for Lorenzo Lotto's Husband and wife," Optical Society of America, San Jose, CA (2007) (abstract)
Shows that the constraints upon the putative optical projector used in Lorenzo Lotto's Husband and wife severely undercut the Hockney/Falco explanation for the use of optical projections. (pdf)
David G. Stork, "Imaging technology enhances the study of art," Vision Systems Design 12(10): 69–73, 2007
A short announcement for the inaugural symposium, Computer image analysis in the study of art. (pdf)
Morteza Shahram, David G. Stork and David L. Donoho, "Recovering layers of brush strokes through statistical analysis of color and shape: An application to van Gogh’s Self portrait in a grey felt hat," SPIE Electronic Imaging: Computer image analysis in the study of art, vol. 6810, David G. Stork and Jim Coddington (eds.), 68100D, SPIE 2008
Describes the "De-picting algorithm," which digitally removes layers of brushstrokes to reveal the stages of development of a painting. (pdf)
Silvio Savarese, Ron Spronk, David G. Stork and Andrey DelPozo, "Reflections on praxis and facture in a devotional portrait diptych: A computer analysis of the mirror in Hans Memling's Virgin and Child and Maarten van Nieuwenhove," SPIE Electronic imaging: Computer image analysis in the study of art, vol. 6810, David G. Stork and Jim Coddington (eds.), 68100G, SPIE 2008
Uses computer graphics to construct a tableau virtuel of the diptych to reveal that the convex mirror was likely added as an afterthought. (pdf)
M. Dirk Robinson and David G. Stork, "Aberration analysis of the putative projector for Lorenzo Lotto's Husband and wife: Image analysis through computer ray-tracing," SPIE Electronic imaging: Computer image analysis in the study of art, vol. 6810, David G. Stork and Jim Coddington (eds.), 68100H, SPIE 2008
Shows that the presence of a 116-cm-wide canvas (screen) in Lotto's putative projector precludes the kind of depth-of-field problems central to the Hockney/Falco optical explanation for this work, thereby rebutting their claim.(pdf)
Micah K. Johnson, David G. Stork, Soma Biswas and Yasuo Furuichi, "Inferring illumination direction estimated from disparate sources in paintings: An investigation into Jan Vermeer's Girl with a pearl earring," SPIE Electronic imaging: Computer image analysis in the study of art, vol. 6810, David G. Stork and Jim Coddington (eds.), 68100I, SPIE 2008
Shows the high agreement between direction of illumination estimated from cast shadows, occluding contours, shape-from-shading, and computer graphics methods on this Vermeer portrait. (pdf)
David G. Stork and Yasuo Furuichi, "Image analysis of paintings by computer graphics synthesis: An investigation of the illumination in Georges de la Tour's Christ in the carpenter's studio," SPIE Electronic imaging: Computer image analysis in the study of art, vol. 6810, David G. Stork and Jim Coddington (eds.), 68100J, SPIE 2008
Uses computer graphics to show that the illumination in this painting was at the candle and not, as Hockney claims, "outside the frame" or "in place of the other figure." Shows that the cast shadow of Christ's left shin is far more consistent with the illuminant in place of the candle than with Hockney's claim that it was "in place of the other figure [St. Joseph]," thereby corroborating previous analyses rejecting the optical tracing claim for this painting. (pdf)
David G. Stork and Jim Coddington (eds.) Computer image analysis in the study of art, SPIE 2008
The first symposium proceedings in this young field. (Order here.)
Shorter publications

When computers look at art:
Image analysis in humanistic studies of the visual arts


David G. Stork

Ricoh Innovations and Stanford University

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.

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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.

Joint work with Antonio Criminisi, Andrey DelPozo, David Donoho, Marco Duarte, Micah Johnson, Dirk Robinson, Silvio Savarese, Morteza Shahram, Ron Spronk, Christopher W. Tyler and Yasuo Furuichi

Is David Hockney right?
Did early Renaissance masters trace optical images?


David G. Stork

Ricoh Innovations and Stanford University

In 2001, artist David Hockney and scientist Charles Falco stunned the art world with a theory that, if correct, would profoundly alter our view of the development of image making. They claimed that as early as 1430, some Renaissance artists employed optical devices such as concave mirrors to project images onto their canvases, which they then traced or painted over. In this way, the theory attempts to explain the newfound heightened naturalism or "opticality" of painters such as Jan van Eyck, Robert Campin, Hans Holbein the Younger, and many others.

This talk for general audiences, profusely illustrated with Renaissance paintings, will present the results of the first independent examinations of the Hockney/Falco theory. It covers basic geometrical optics of image formation, shadows and perspective as well as 15th-century technology with special emphasis on Lotto's Husband and wife (1543), van Eyck's Portrait of Arnolfini and his wife (1434), Caravaggio's Supper at Emmaus (1596-8) and Campin's Mérode Altarpiece (1425). While there remain some loose ends, an analysis of the paintings, infra-red reflectograms, modern reenactments, internal consistency of the theory, and alternate explanations allows us to judge with high confidence the plausibility of this new theory. You may never see Renaissance paintings the same way again.

Joint work with Antonio Criminisi, Marco Duarte, Micah Johnson, Dirk Robinson, Christopher W. Tyler and Yasuo Furuichi

Presentations
  1. Stanford University Department of Art History, seminar (3/02)
  2. Stanford University Department of Computer Science, Computer Graphics Group, seminar (5/02)
  3. Cantor Center for the Arts at Stanford University, public lecture (9/02)
  4. Carnegie-Mellon University, Department of Art and Art History, colloquium (9/02)
  5. Society for Literature and Science, Pasadena CA, conference paper (10/02)
  6. Optical Society of Northern California, public lecture (11/02)
  7. University of Maryland, Department of Physics, colloquium (2/03)
  8. University of Rochester, Institute of Optics, colloquium (2/03)
  9. Rochester Institute of Technology, Center for Imaging Science, colloquium (2/03)
  10. Oxford University, Workshop on Optics and Art, seminar (3/03)
  11. Microsoft Research Cambridge UK, seminar (3/03)
  12. Courtauld Institute London, seminar (3/03)
  13. University of Washington, Department of Physics, colloquium (4/03)
  14. Microsoft Research Redmond WA, seminar (4/03)
  15. Stanford University, Department of Physics and Applied Physics, colloquium (4/03)
  16. NASA Goddard Engineering Division, colloquium (5/03)
  17. Rochester Institute of Technology, special public lecture (5/03)
  18. Adobe Corporation, colloquium (07/03)
  19. PARC Forum (07/03)
  20. Sonoma State University, Department of Physics and Astronomy, colloquium (9/03)
  21. San Jose State University, Department of Physics, colloquium (10/03)
  22. U. Colorado Boulder, Optical Science and Engineering Program, colloquium (10/03)
  23. University of Oregon, Department of Physics, colloquium (10/03)
  24. Color Imaging Conference 11, plenary lecture (11/03)
  25. SPIE Electronic Imaging, invited lecture (1/04)
  26. SPIE Electronic Imaging, contributed talk (1/04)
  27. Bay Area Vision Meeting, contributed talk (3/04)
  28. Cantor Center for the Arts at Stanford University, special course lecture (4/04)
  29. Optical Society of America Rochester Section Annual dinner, special lecture (4/04)
  30. The Arts at St. Bede's, special lecture (5/04)
  31. University of California at Santa Cruz, colloquium (10/04)
  32. Optics and Renaissance painting symposium, Optical Society of America Annual Meeting, Rochester NY, invited lecture (10/04)
  33. SPIE Electronic Imaging, invited lecture (1/05)
  34. SPIE Electronic Imaging, contributed talk (1/05)
  35. SPIE Electronic Imaging, contributed talk (1/05)
  36. University of California at Berkeley, colloquium (2/05)
  37. Arizona State University, Departments of Physics and Psychology, colloquium (3/05)
  38. NASA Ames Research Center, colloquium (3/05)
  39. Florida Artificial Intelligence Research Symposium, plenary lecture (5/05)
  40. Politecnico di Milano, Milan IT, public lecture (6/05)
  41. Angel Art Academy, Florence IT, public lecture (6/05)
  42. Xerox Corporation, El Segundo CA, distinguished lecture (9/05)
  43. International Conference on Image Processing, Genoa Italy, short course (9/05)
  44. University of Pennsylvania, distinguished lecture (10/05)
  45. University of Delaware, colloquium (10/05)
  46. Metropolitan Museum of Art, public lecture (10/05)
  47. Mitsubishi Electric Research Lab (MERL), colloquium (10/05)
  48. Harvard University, seminar (10/05)
  49. Duke University, colloquium (12/05)
  50. Stanford University, colloquium (2/06)
  51. University of Illinois-Champaign Urbana, colloquium (2/06)
  52. Columbia University, distinguished lecture (2/06)
  53. Rutgers University, colloquium (2/06)
  54. New York University, seminar (2/06)
  55. Machines that learn workshop, Snowbird UT, banquet lecture (4/06)
  56. Belvédère Museum, Heerenveen Netherlands, public lecture (4/06)
  57. Pattern recognition for the security community, Washington DC, lecture (4/06)
  58. Wadsworth Atheneum, Hartford CT, Docent Memorial Lecture (4/06)
  59. Sony Research Labs, Paris, seminar (7/06)
  60. Imperial College London, Department of Physics, colloquium (7/06)
  61. National Gallery London, public lecture (7/06)
  62. Cambridge University, Department of Engineering, colloquium (7/06)
  63. SPIE Optics and Photonics, contributed talk (8/06)
  64. International Conference on Pattern Recognition, Hong Kong, short course (8/06)
  65. International Conference on Pattern Recognition, Hong Kong, contributed paper (8/06)
  66. Carleton University, Ottawa Ontario, Department of Art History, special lecture (9/06)
  67. University of California Santa Barbara, Department of Computer Science, colloquium (9/06)
  68. Rensselaer Polytechnic Institute, Troy NY, Department of Physics, colloquium (10/06)
  69. Optical Society of America Annual Meeting, Optical Design Symposium, lecture (10/06)
  70. San Jose State University, San Jose CA, Nexus of Science and Art, seminar (11/06)
  71. Rice University, Department of Electrical Engineering, colloquium (11/06)
  72. Harvard University, Fogg Art Museum, seminar (12/06)
  73. Massachusetts Institute of Technology, MIT Media Lab, colloquium (12/06)
  74. Massachusetts Institute of Technology, Artificial Intelligence Lab, colloquium (12/06)
  75. Boston University, CELEST Science of Learning series, seminar (12/06)
  76. American Association of Physics Teachers Annual Meeting, Seattle WA, invited lecture (1/07)
  77. Gage Art Academy and Frye Art Gallery, Seattle WA, public lecture (1/07)
  78. University of Washington, Seattle, colloquium (1/07)
  79. University of California, Irvine, Department of Computer Science, colloquium (1/07)
  80. SPIE Electronic Imaging, San Jose CA, short course (1/07)
  81. SPIE Electronic Imaging, San Jose CA, contributed paper (1/07)
  82. University of Maryland, College Park, Department of Computer Science, distinguished lecture (3/07)
  83. Lehigh University, Department of Computer Science and Engineering, distinguished seminar (4/07)
  84. University of Illinois, Chicago, seminar (5/07)
  85. Art Institute of Chicago, seminar (6/07)
  86. Museum of Modern Art, seminar (8/07)
  87. Venice Biennale, public lecture (9/07)
  88. International Conference on Image Analysis and Processing, short course (9/07)
  89. The Louvre, seminar (9/07)
  90. CREATE (Colour Research for European Advanced Technology Employment), Bristol UK, invited lecture (9/07)
  91. Nokia Research, colloquium (10/07)
  92. Yahoo! Research Berkeley, seminar (10/07)
  93. University of Wisconsin, Madison, seminar (11/07)
  94. SPIE Electronic Imaging, short course SC814 (1/08)
  95. SPIE Electronic Imaging, Special Symposium, Computer image analysis in the study of art, contributed talk (1/08)
  96. SPIE Electronic Imaging, Special Symposium, Computer image analysis in the study of art, contributed talk (1/08)
  97. SPIE Electronic Imaging, Special Symposium, Computer image analysis in the study of art, contributed talk (1/08)
  98. SPIE Electronic Imaging, Special Symposium, Computer image analysis in the study of art, contributed talk (1/08)
  99. SPIE Electronic Imaging, Special Symposium, Computer image analysis in the study of art, contributed talk (1/08)
  100. San Jose Museum of Art, seminar (2/08)
  101. Newcastle University, colloquium (2/08)
  102. Institute for Conservation, London, public lecture (2/08)
  103. van Gogh Museum, Amsterdam, seminar (2/08)
  104. The Mauritshuis, The Hague, public lecture (2/08)
  105. Technical University of Delft, colloquium (2/08)
  106. CWI, Department of Computer Science, Amsterdam, colloquium (2/08)
  107. University of Modena, Italy, colloquium (2/08)
  108. Princeton University, seminar (2/08)
  109. Princeton University, SlashArts, public lecture (2/08)
  110. University of Delaware, Winterthur Conservation Center, lecture (2/08)
  111. Stanford University, Department of Electrical Engineering, colloquium (3/08)
  112. University of California Los Angeles, Department of Computer Science, colloquium (3/08)
  113. Café Scientifique, public presentation and open discussion (3/08)
  114. Kodak Research Labs, Rochester NY, colloquium (3/08)
  115. University of Rochester, Department of Computer Science, colloquium (3/08)
  116. Rochester Institute of Technology, Center for Imaging Science, seminar (3/08)
  117. Sony Research Labs, California, seminar (4/08)
  118. George Mason University, Department of Computer Science, Arlington VA, colloquium (5/08)
  119. University of Tokyo, colloquium (5/08)
  120. de Young Museum, San Francisco CA, seminar (6/08)
  121. Stanford Linear Accelerator Center, colloquium (6/08)
  122. Computer Vision and Pattern Recognition Conference, Anchorage AK, short course (6/08)
  123. Chilmark Public Library, Chilmark MA, public lecture (7/08)
  124. "Ask a scientist," San Francisco, public presentation (9/08)
  125. Silicon Valley Innovation Institute, public lecture (9/08)
  126. University of Redlands, Redlands CA, President's High Table lecture (9/08)
  127. Getty Research Institute, Santa Monica CA, seminar (9/08)
  128. Image processing for artist identification, van Gogh Museum, plenary lecture (10/08)
  129. San Jose State University, colloquium (11/08)
Short course description: Computer Vision, Image Understanding, and the Analysis of Master Drawings and Paintings

Computer Vision, Image Understanding, and the Analysis of Master Drawings and Paintings

This course is an introduction to the application of computer vision and image analysis to problems in art and art history, specifically realist art. Realist paintings are a rich source of information, both of the scene portrayed and the techniques the artist used to render that scene. Students will learn the principles of perspective and how to apply perspective analysis to paintings to infer vanishing points, locate perspective inconsistencies and to determine whether the artist used perspective constructions or tools. Students will learn how to infer the number, color, and position of light sources based on position, color and blur of cast shadows and highlights along occluding boundaries. Students will learn how to estimate sizes of depicted objects based on perspective and fiducial or reference objects or relationships. Students will learn how to estimate "camera parameters" of the artist (or imaging system), such as the effective magnification, focal length and in some cases aberrations. Some of these methods require no more than ruler and pencil, others require commercial software (e.g., Adobe Illustrator), others were adapted from their use in forensic analysis of digital photographs and require powerful commercial image processing packages (including ones based on C++, Matlab, Mathematica), and yet others require researchers to write special code. This course will be excellent introduction and background for research presented in symposium EI122, "Computer image analysis in the study of art."

LEARNING OUTCOMES
This course will enable you to:

INTENDED AUDIENCE

Image processing and computer vision researchers interested in rigorous image analysis and art, as well as conservators and curators seeking new analytical techniques. Prior knowledge of basic art history and media to the level of a college survey course is desirable, but will not be assumed. Familiarity with commercial image software such as Adobe Photoshop is essential; knowledge of image processing and computer vision packages and languages such as Matlab, Mathematica and C++ is desirable, but not essential.

COURSE LEVEL

Introductory

INSTRUCTOR

David Stork is Chief Scientist of Ricoh Innovations and Consulting Professor at Stanford University. He has published six books and proceedings volumes, including Pattern Classification (2nd ed), Seeing the Light, HAL's Legacy and Computer image analysis in the study of art. He and his colleagues have pioneered the application of rigorous computer image analysis in the study of art and he has lectured widely on the topic and major art museums worldwide. He is a member of IEEE, SPIE, ACM and OSA and co-chair of the 2008 symposium SPIE EI122, "Computer image analysis in the study of art."

Other websites
Acknowledgements
I have profited from discussion, correspondence and in some cases collaboration with David Andrzejewski (University of Wisconsin), Michael John Angel (Angel Art Academy, Florence), Irina Artemieva (Hermitage Museum), Rachel Billinge (National Gallery London), Stephanie Buck (Frei Universität Berlin), Edwin Buijsen (Rijksbureau voor Kunsthistorische Documentatie), Lorne Campbell (National Gallery London), Jim Coddington (Museum of Modern Art), Antonio Criminisi (Microsoft Research Cambridge), David Donoho (Stanford University), Sven Dupré (Ghent University), Sam Edgerton (Williams College), Gary Faigin (Gage Art Academy), Molly Ann Faries (Indiana University), Yasuo Furuichi (Kanagawa, Japan), Michael John Gorman (Arkimedia Dublin), John Grievenkamp (University of Arizona), Peter Humphrey (University of St. Andrews), Vincent Ilardi (University of Massachusetts), Amy Ione (Diatrope.com), M. Kimo Johnson (Massachusetts Institute of Technology), Martin Kemp (Oxford University), Thomas Ketelsen (Kupferstich Kabinett Dresden), Alexander J. Kossolapov (Hermitage Museum), David C. Lindberg (University of Wisconsin), Christof Lüthy (Radboud Universiteit Nijmegen), Walter Liedtke (Metropolitan Museum of Art), Ann James Massey (Independent painter, France), Pamela O. Long (American Association of Historians), Elke Oberthaler (Kunsthistorisches Museum Vienna), Lynda Pigeon (Barley Hall Museum, York UK), Monique de Ruette (Musées Royaux d'Art et d'Histoire Brussels), Silvio Savarese (University of Illinois, Urbana-Champaign), Sara Schechner (Harvard University), James Schoenberg (J & J Graphics), Morteza Shahram (Stanford University), John Spike (Independent scholar, Florence), Brandon Smith (University of Wisconsin), Ron Spronk (Queen's University), Philip Steadman (University College London), David Stone (University of Delaware), Richard Stone (Metropolitan Museum of Art), Timothy Stotz (Studio Escalier), Richard Taylor (University of Oregon), Christopher W. Tyler (Smith-Kettlewell Eye Research Institute), John Varianno (Mt. Holyoke College), Nicholas Williams (Independent painter, UK), Li Zhang (University of Wisconsin), and Jerry Zhu (University of Wisconsin), as well as students in my classes ART216A, "Optics, perspective and Renaissance painting," and CS379D, "Computer vision and image analysis in the study of art," at Stanford University. The views and analyses in this site and linked papers are those of their authors and may or may not reflect the views of individuals just listed.
Biographical sketch
Dr. David G. Stork is Chief Scientist of Ricoh Innovations and Consulting Professor at Stanford University, where he has held appointments, taught, and sat on dissertation committees frequently over the last 18 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. He has published in optics and art for over two decades, including Seeing the Light: Optics in nature, photography, color, vision and holography (Wiley), the leading textbook on optics in the arts. 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 has taught courses such as "Light, color and visual phenomena," "The physics of aesthetics and perception," "Optics, perspective and Renaissance painting," and "Computer vision and image analysis in the study of art" over the last quarter century variously at leading liberal arts and research universities such as Wellesley College, Swarthmore College, Clark University and Stanford University. He is co-editor of Computer image analysis in the study of art (SPIE 2008), the first symposium volume on the topic. He holds 37 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, as well as six books and proceedings volumes, including Pattern Classification (2nd ed.), the world's all-time best-selling textbook in the field, translated into three languages and used in courses in over 250 universites worldwide. 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 200 traditional invited colloquia and seminars). He created the PBS television documentary 2001: HAL's Legacy, based on his book HAL's Legacy: 2001's computer as dream and reality (MIT). He was one of four scientists invited to comment on Mr. Hockney's theory at the December 2001 "Art and Optics" Symposium at the New York Institute for the Humanities and one of two scientists invited to present a lecture in the symposium exploring the possible use of optics by early Renaissance painters at the Optical Society of America's Annual Meeting in Rochester, NY, October 2004.
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