New American website can identify birds from photographs
A Blackburnian Warbler is defined by points on its body that the software can compare with input data © Cornell University
A remarkable new aid to birdwatchers has been developed that enables computers to identify hundreds of US and Canadian bird species in photographs.
The bird photo identifier, developed by the Visipedia research project in collaboration with the Cornell Lab of Ornithology, is available for free at: AllAboutBirds.org/photoID
Called Merlin Bird Photo ID, the identifier is capable of recognising 400 of the mostly commonly encountered birds in the United States and Canada.
“It gets the bird right in the top three results about 90 per cent of the time, and it’s designed to keep improving the more people use it,” says Jessie Barry at the Cornell Lab of Ornithology.
“That’s truly amazing, considering that the computer vision community started working on the challenge of bird identification only a few years ago.”
To see if Merlin can identify the bird in an image you upload it with information on where and when you took the photo. To orient the software you draw a box around the bird and click on its bill, eye, and tail.
Within seconds, Merlin combines powerful artificial intelligence techniques with millions of data points input by humans, then presents the most likely species, including additional photos and sounds.
“Computers can process images much more efficiently than humans,” says Serge Belongie, a professor of Computer Science at Cornell Tech.
"They can organise, index, and match vast constellations of visual information such as the colors of the feathers and shapes of the bill.
“The state-of-the-art in computer vision is rapidly approaching that of human perception, and with a little help from the user we can close the remaining gap and deliver a surprisingly accurate solution.”
Merlin’s success relies on collaboration between computers and humans. The computer learns to recognise each species from tens of thousands of images identified and labeled by bird enthusiasts.
It also taps into more than 70 million sightings recorded by birders in the eBird.org database, narrowing its search to the species found at the location and time of year when the photo was taken.
Because the photo identifier uses machine-learning techniques, it has the potential to improve the more people use it.
After it can reliably identify photos taken with smartphones, the team will add it to the Merlin Bird ID app, a free app that has helped users with more than one million bird identifications by asking them five questions.
Merlin's computer vision system was developed by Steve Branson and Grant Van Horn of the Visipedia project, led by professors Pietro Perona at the California Institute of Technology and Serge Belongie at Cornell Tech.
Their work was made possible with support from Google, the Jacobs Technion-Cornell Institute at Cornell Tech, and the National Science Foundation.
