Illustration by Katie McBride

[Editor’s note: This piece is excerpted from an article in The Conversation and is reprinted with the author’s permission.]

As a birder, I had heard that if you paid careful attention to the head feathers on the downy woodpeckers that visited your bird feeders, you could begin to recognize individual birds. This intrigued me. I even went so far as to try sketching birds at my own feeders and had found this to be true, up to a point.

In the meantime, in my day job as a computer scientist, I knew that other researchers had used machine learning techniques to recognize individual faces in digital images with a high degree of accuracy.

These projects got me thinking about ways to combine my hobby with my day job. Would it be possible to apply those techniques to identify individual birds?

So, I built a tool to collect data: a type of bird feeder favored by woodpeckers and a motion-activated camera. I set up my monitoring station in my suburban Virginia yard and waited for the birds to show up.

Identifying birds in images is an example of a “fine-grained classification” task, meaning that the algorithm tries to discriminate between objects that are only slightly different from each other. Many birds that show up at feeders are roughly the same shape, for example, so telling the difference between one species and another can be quite challenging, even for experienced human observers.

The challenge only ramps up when you try to identify individuals. For most species, it simply isn’t possible. The woodpeckers that I was interested in have strongly patterned plumage but are still largely similar from individual to individual.

So, one of our biggest challenges was the human task of labeling the data to train our classifier. I found that the head feathers of downy woodpeckers weren’t a reliable way to distinguish between individuals because those feathers move around a lot. They’re used by the birds to express irritation or alarm. However, the patterns of spots on the folded wings are more consistent and seemed to work just fine to tell one from another. Those wing feathers were almost always visible in our images, while the head patterns could be obscured depending on the angle of the bird’s head.

In the end, we had 2,450 pictures of eight different woodpeckers. When it came to identifying individual woodpeckers, our experiments achieved 97 percent accuracy. However, that result needs further verification.