Everyone may be a critic, but now Penn State researchers are paving a way for machines to get in on the act. However, the researchers add that their photo-analysis algorithm is designed to offer constructive feedback, not to replace photographers.
The researchers have developed an algorithm that analyses the arrangement of visual elements—the composition—of digital photographs. It also offers feedback about the perceived composition of the photograph and provides examples of similarly composed pictures of high aesthetic value, said James Wang, professor of information sciences and technology. Wang and colleagues recently received a patent for the system. "If you think about aesthetics, everything is about composition," said Wang. "You can look into colours, or textures, or shapes, but, if you boil it down, you eventually have to consider all of these elements as part of composition."
Training a machine to become an art critic is not easy, according to the researchers. A machine must be trained with examples of highly regarded photographs in order to recognize good compositional elements, said Jia Li, professor of statistics, who worked with Wang.
The original article can be found at Phys.org.
The original source can be found at Penn State University.
(Score: 2) by hendrikboom on Sunday August 16 2015, @05:47PM
So what happens when you combine this with Google's image synthesis program? You know, the one that filters random noise and improves its rating so as te eventuallly, if it has been trained on coffee cans, presents a random mess of coffee can parts? Will we get a random excellent composition?