C. Richard Johnson, Jr.– Weave Maps and Rollmates: Computational Analysis of European Old Master Canvases and Early Chinese Silk Paintings

One method of connecting a pair of paintings is to establish that they are painted on two pieces of fabric originally from the same roll. Rollmate pairings can offer insight into issues of dating, attribution, and artist’s intent. A computational procedure developed and applied over the past decade provides a method for identifying rollmates based on color-coded maps providing full painting coverage of spot thread densities automatically extracted from high resolution images. These weave maps display striped patterns shared by other fabric from the same roll that can serve as a key indicator of rollmate status.  This talk introduces the concept of thread count automation for a simple weave and the visualization of the results as weave maps. Display of a variety of discovered matches spanning the 15th through the 19th centuries of Old Master European paintings, and evidence that this approach to rollmate identification applies to early (12th – 13th century) silk paintings, illustrates the breadth of utility of this pioneering effort in computational art history.

C. Richard Johnson, Jr. received the first PhD minor in Art History granted by Stanford University along with a PhD in Electrical Engineering in 1977.  Forty years later, he is the Jacobs Fellow in Computational Arts and Humanities at the Jacobs Technion-Cornell Institute at Cornell Tech (New York, NY) and the Geoffrey S. M. Hedrick Senior Professor of Engineering at Cornell University (Ithaca, NY).  He is also currently a Visiting Research Scholar in the Conservation Center of the Institute of Fine Arts at New York University, a Scientific Researcher of the Rijksmuseum, and Computational Art History Advisor to the RKD (Netherlands Institute for Art History). Professor Johnson has founded four projects with cooperating research teams with the goal of characterizing and matching manufactured patterns in art supports: canvas thread count automation (in 2007), historic photographic paper classification (in 2010), laid paper chain line pattern marking and matching (in 2012), and watermark identification in Rembrandt’s etchings according to Hinterding’s taxonomy (in 2015).











When: Fri., Sep. 29, 2017 at 12:30 pm - 1:45 pm
Where: Columbia University
116th St. & Broadway
212-854-1754
Price: Free
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One method of connecting a pair of paintings is to establish that they are painted on two pieces of fabric originally from the same roll. Rollmate pairings can offer insight into issues of dating, attribution, and artist’s intent. A computational procedure developed and applied over the past decade provides a method for identifying rollmates based on color-coded maps providing full painting coverage of spot thread densities automatically extracted from high resolution images. These weave maps display striped patterns shared by other fabric from the same roll that can serve as a key indicator of rollmate status.  This talk introduces the concept of thread count automation for a simple weave and the visualization of the results as weave maps. Display of a variety of discovered matches spanning the 15th through the 19th centuries of Old Master European paintings, and evidence that this approach to rollmate identification applies to early (12th – 13th century) silk paintings, illustrates the breadth of utility of this pioneering effort in computational art history.

C. Richard Johnson, Jr. received the first PhD minor in Art History granted by Stanford University along with a PhD in Electrical Engineering in 1977.  Forty years later, he is the Jacobs Fellow in Computational Arts and Humanities at the Jacobs Technion-Cornell Institute at Cornell Tech (New York, NY) and the Geoffrey S. M. Hedrick Senior Professor of Engineering at Cornell University (Ithaca, NY).  He is also currently a Visiting Research Scholar in the Conservation Center of the Institute of Fine Arts at New York University, a Scientific Researcher of the Rijksmuseum, and Computational Art History Advisor to the RKD (Netherlands Institute for Art History). Professor Johnson has founded four projects with cooperating research teams with the goal of characterizing and matching manufactured patterns in art supports: canvas thread count automation (in 2007), historic photographic paper classification (in 2010), laid paper chain line pattern marking and matching (in 2012), and watermark identification in Rembrandt’s etchings according to Hinterding’s taxonomy (in 2015).