38. PHAROS: An International Consortium of Photo Archives
• Bibliotheca Hertziana, Rome (1,065,000)
• Bildarchiv Foto Marburg, Germany (2,000,000)
• Courtauld Institute of Art, London (4,173,500)
• Fondazione Federico Zeri, Bologna (290,000)
• Frick Art Reference Library, New York (1,346,000)
• Getty Research Institute, Los Angeles (2,086,000)
• Villa I Tatti, Florence (239,000)
• Institut National d’Histoire de l’Art, Paris (750,000)
• Kunsthistorisches Institut, Florence (650,000)
• National Gallery of Art, Washington (7,600,000)
• Paul Mellon Centre, London (185,000)
• Rijksbureau, The Hague (7,000,000
• Warburg Institute, London (3,500,000)
• Yale Center for British Art, New Haven (132,000)
44. Idyll: Offline Image Cropping
• Crop and annotate images offline and on a
mobile device.
• Saves the selections back to a server.
45.
46.
47.
48. ComputerVision
• Unsupervised (requires no labeling):
• Comparing an entire image
• Categorizing an image
• Supervised (requires labeling):
• Finding parts of an image
• Finding and categorizing parts of an image
49. Unsupervised Training
• Requires little-to-no prepping of data
• Can just give the tool a set of images and
have it produce results
• Extremely easy to get started, results aren’t
always as interesting.
• Unsupervised: MatchEngine, PasteC
50. Supervised Training
• Need lots of training data
• Needs to be pre-selected/categorized
• Think:Thousands of images.
• If your collection is smaller than this, perhaps
it may not benefit.
• Or you may need crowd sourcing.
• Results can be more interesting:
• “Find all the people in this image”
51. General Computer
Vision
• Ideal for some supervised training problems
• CCV
• http://libccv.org/
• https://github.com/liuliu/ccv
• OpenCV
• http://opencv.org/