14Dec/19Off
A new algorithm reveals a web of artistic connections by looking for humans posed similarly in different paintings.
The method is relatively straightforward and based on the vast databases that art historians have created in recent years. These have digitized the collections from many of the world’s top museums and galleries, and many of them are openly available online. These databases are suddenly amenable to analysis by machine intelligence.
At the same time, other researchers have been developing machine vision algorithms that can determine a human pose from a 2D image. Probably the most advanced is an algorithm called OpenPose, an open-source program for real-time pose detection in 2D images, developed at Carnegie Mellon University in Pittsburgh.
They say the automated process easily outperforms other ways of finding similar images.