What can machine learning tell us about the rock art in Arnhem Land?

Computers compare minute style details.

South Australian researchers, led by Daryl Wesley of Flinders University, working with the Mimal and Marrku traditional owners of the Wilton River area in the Northern Territory, took a look at rock art in Arnhem Land to examine how it transformed stylistically over time.

The team used machine learning to analyse images of different styles and subjects, to see how similar they were at a minute level, and determine the chronology of art evolution.

“One amazing outcome is that the machine learning approach ordered the styles in the same chronology that archaeologists have ordered them in by inspecting which appear on top of which,” says Jarrad Kowlesser, one of the researchers at Flinders University. “This shows that similarity and time are closely linked in the Arnhem Land rock art and that human figures drawn closer in time were more similar to one another than those drawn a long time apart.

“For example, the machine learning algorithm has plotted Northern Running Figures and Dynamic Figures very close to one another on the graph it produces.

“This shows that these styles which we know are closer to each other in age are also closer to each other in appearance, which might be a very hard thing to notice without an approach like this.”

The team first taught the computer how to recognise different images by using an existing dataset of 14 million photos of animals and objects. This model was then applied to the rock art images. The results are published in Australian

Archaeology. The code has been made available via Github.