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Artificial intelligence may be able to settle the debate over how many people attend protests or gatherings.

Vast numbers of people took to the streets of London this weekend to call for a second referendum on the UK’s membership of the European Union. But exactly how many people were there is up for debate. Protest organisers say there were 1 million people, but when similar claims were made earlier in the year, they were disputed by fact-checking organisations.

A method developed by Reza Bahmanyar at the German Aerospace Center and his colleagues that uses artificial intelligence could help improve counts in the future.


To create the system, the team hand-counted nearly a quarter of a million people in 33 images taken from planes, drones and helicopters, then used this to train an algorithm called MRCNet. MRCNet divides each image into small squares and analyses how many people are in each one.

The results are better than other AI-powered crowd estimation systems, proving 15 percent more accurate than its nearest competitor at reaching the correct number in a crowd. The system is much faster than hand annotation, taking 0.03 milliseconds to compute the number of people in each square.

At present, the team have only used the AI in lab conditions, but Bahmanyar hopes to soon mount the system onto planes and helicopters to do real-time counts.

Crowd science is inexact and slow to come up with estimates. “It’s a highly emotive topic,” says Keith Still at Manchester Metropolitan University, UK. Still invented one of the current best methods for measuring crowds, which monitors the routes people take, the density of the crowd and the profile of the participants to get an accurate estimate of numbers.

“I think in the right places, this technology could be really useful,” says Still. “Protest organisers and governments often don’t want real numbers,” he says. “They want marketing numbers. Will they invest in something that punctures their claim?”

Reference: arxiv.org/abs/1909.12743