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Automated Aesthetic Judgments

How would you rate this image?

James Z. Wang, associate professor of information sciences and technology, is one of the principal researchers on the Aesthetic Quality Inference Engine (ACQUINE), a system that judges the aesthetic quality of digital images. Wang said this tool is a significant first step in recognizing human emotional reaction to visual stimulus.

ACQUINE, which has been in development since 2005 and was launched in April 2009, can be found online at http://acquine.alipr.com. Users can upload their own images for rating or test the system by providing a link to any image online. The system provides an aesthetic rating within seconds. more…

By mmacken

twitter: meganmacken

Director, Visual Resources Center and Digital Media Archive, Division of the Humanities, The University of Chicago.

My academic background ranges from classics and comparative literature to modern art and architectural history, and so, naturally, I am a librarian. I have graduate degrees in art history and library science, manage digital image and audio collections for the Division of the Humanities, and am always eager to collaborate across disciplines, universities, and even continents! I'm interested in exploring the library's role in Digital Humanities, not just as an archive for born-digital objects but as a locus for Digital Humanities centers. At THATCamp I'm excited to find out how others are visualizing data, especially to facilitate creative research and teaching in art and architectural history and film studies. How can visual data (still images, film, 3D models, etc) move beyond illustration and become a source for research? What kind of creative information retrieval interfaces do we need to do this? We've got metadata...let's make it work!

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