AI is capable of picking faces out of the crowd — even if that crowd is squabbling over bananas in a jungle.
What’s new: Researchers at the University of Oxford developed a face recognition app that identifies individual chimpanzees in footage shot in the wilds of Guinea. The work could give wildlife conservation efforts a powerful new tool.
How it works: The group adapted the VGG-M convolutional neural network architecture. They trained the model on roughly 50 hours of footage representing 23 individuals over 14 years.
- The model identified apes as they aged.
- It was able to recognize individuals regardless of low light, poor image quality, and facing away from the camera.
- The researchers pitted their model against a human trained to recognize chimps. The human sorted 42 percent of the images correctly. The model’s accuracy was 84 percent.
Behind the news: Zoologists have embraced image recognition for conservation efforts. The technology is counting giraffes in Africa and tracking wolverines in the Pacific Northwest. An innovative application called WildBook that trawls YouTube for wildlife videos has been used to catalog whale shark migrations.
Why it matters: Chimpanzees, like humans, are highly social animals. The ability to track individuals enabled the researchers to map the tribe’s structure. The model generalized well to other primate species in preliminary tests. The researchers suggest that their approach could be used with other animals where a sufficient video record exists.
We’re thinking: Applications like this could help cash-strapped conservation efforts to focus on translating data into action, and reduce the need for invasive, labor-intensive methods like tagging animals with RFID.