Look at the crowd above. How many people would you say were in the photo? How long do you think it might take you to count them? And if it was just a small part of a bigger crowd, what is the calculation to estimate how many people were there altogether? It’s a tough call, isn’t it? So, you now have a little insight into the way crowd counting used to happen – arduously, undertaken by humans and, as a result, somewhat lacking in the accuracy department. Today, however, things are pretty different.
Crowd counting is important. We all want to be able to live our daily lives in a way that is safe and convenient and knowing how many people are in a given space at any time can sometimes be essential to this. People in charge of spaces and places need to manage the movement of large numbers of people, as well as plan the resources needed to look after them. So, where there are huge crowds of people – concerts, sports events and festivals, for example – there is crowd counting. But it’s also critically important for public spaces, such as airports, train stations and shopping centres. As you might imagine, these are places where manual counting just isn’t ideal.
Back in 2016, Canon released a piece of software called People Counter, which uses video content analysis technology to count the number of people present in images captured by network cameras. Later, in 2019, this was followed by an updated version (called Crowd People Counter) which was able to count thousands of people in seconds, thanks to developments in Artificial Intelligence. A proof of concept at an international rugby match in 2018 showed that it could count around 6000 people in just a few seconds with a margin of error below 5%, when compared to manual counting.