Conservation biologists invest a huge amount of time reviewing camera trap images, and – even worse – a huge fraction of that time is spent reviewing images they aren't interested in. This primarily includes empty images, but for many projects, images of people and vehicles are also "noise", or at least need to be handled separately from animals.
Machine learning can accelerate this process, letting biologists spend their time on the images that matter.
To this end, a team of collaborators trained an AI model – called "MegaDetector" – to detect animals, people, and vehicles in camera trap images. The model's ability to sort and categorize images provides researchers with a significant time savings over doing this work manually.
This page summarizes how the MegaDetector model helps researchers, typically ecologists, who are overwhelmed by camera trap images. It also provides links to a more technical description on how to use MegaDetector.