Melanie Clapham is not the average person. As a bear biologist, she has spent over a decade studying these grizzly bears, who live in Knight Inlet in British Columbia, Canada, and developed a sense for who is who by paying attention to little things that make them different.
“I use individual characteristics — say, one bear has a nick in its ear or a scar on the nose,” she said.
But Clapham knows most people don’t have her eye for detail, and the bears’ appearances change dramatically over the course of a year — such as when they get winter coats and fatten up before denning — which makes it even harder to distinguish between, say, Toffee
and Blonde Teddy
Tracking individual bears is important, she explained, because it can help with research and conservation of the species; knowing which bear is which could even help with problems like figuring out if a certain grizzly is getting into garbage cans or attacking a farmer’s livestock. Several years ago Clapham began wondering whether a technology typically used to identify humans might be able to help: facial recognition software, which compares measurements between different facial features in one image to those in another.
Clapham teamed up with two Silicon Valley-based tech workers and together they created BearID
, which uses facial-recognition software to monitor grizzly bears. So far, the project has used AI to recognize 132 of the animals individually.
While facial-recognition technology known
as a tool for identifying humans — and a controversial one at that, due to well-known issues regarding privacy, accuracy, and bias
— BearID is one of several efforts to adapt it for animals in the wild and on farms. Proponents of the technology, such as Clapham, say it’s a cheaper, longer-lasting, less invasive (and with animals such as bears, less dangerous) way to track animals than, say, attaching a collar or piercing an ear to attach an RFID tag.
Building a grizzly data set
For Clapham, who’s also a postdoctoral fellow at the Unversity of Victoria, this interest in combining bears and AI has been in the works for years. In 2017 she joined Wildlabs.net
, which connects conservationists with those in the tech community. There, she quickly met Ed Miller and Mary Nguyen — two tech workers in San Jose, California (who happen to be married) who were interested in machine learning and watching grizzlies via live webcam at another popular bear hangout, Brooks Falls
in Alaska’s Katmai National Park.
The trio has since gathered thousands of bear photos from Knight Inlet and Brooks River to create data sets, and adapted existing artificial intelligence software called Dog Hipsterizer
(used, naturally, to add silly mustaches and hats to pictures of dogs) to spot bear faces in their images. Once the faces are detected, they can also use AI to recognize specific bears.
“It does way better than we do,” said Miller.
So far, BearID has collected 4,674 images of grizzly bears; 80% of the images…
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