Researchers have developed Birdsnap, a new iPhone app that is an electronic field guide featuring 500 of the most common bird species.
The free app, developed by researchers at Columbia Engineering, led by computer science professor Peter Belhumeur enables users to identify bird species through uploaded photos, accompanies a visually beautiful, comprehensive website that includes some 50,000 images. Birdsnap which also features birdcalls for each species offers users numerous ways to organize species — alphabetically, by their relationship in the Tree of Life and by the frequency with which they are sighted at a particular place and season.
Birdsnap not only identifies species, but tells you which parts of the bird the algorithm uses to identify each species. Birdsnap then automatically annotates images of the bird to show these distinctive parts — birders call them field marks — so the user can learn what to look for.
The team designed what they call "part-based one-vs-one features," or POOFs, each of which classifies birds of just two species, based on a small part of the body of the bird. The system builds hundreds of POOFs for each pair of species, each based on a different part of the bird, and chooses the parts used by the most accurate POOFs as field marks.
Birdsnap also uses POOFs for identification of uploaded images.
The team also took advantage of the fact that modern cameras, especially those on phones, embed the date and location in their images and used that information to improve classification accuracy. Not only did they come up with a fully automatic method to teach users how to identify visually similar species, but they also designed a system that can pinpoint which birds are arriving, departing, or migrating.
"Our goal is to use computer vision and artificial intelligence to create a digital field guide that will help people learn to recognize birds," says Belhumeur, who launched Leafsnap, a similar electronic field guide for trees, with colleagues two years ago. "We've been able to take an incredible collection of data — thousands of photos of birds — and use technology to organize the data in a useful and fun way".
Belhumeur and his colleague, Computer Science Professor David Jacobs of the University of Maryland, realized that many of the techniques they have developed for face recognition, in work spanning more than a decade, could also be applied to automatic species identification. State-of-the-art face recognition algorithms rely on methods that find correspondences between comparable parts of different faces, so that, for example, a nose is compared to a nose, and an eye to an eye.
Birdsnap works the same way, detecting the parts of a bird so that it can examine the visual similarity of its comparable parts (each species is labelled through the location of 17 parts). It automatically discovers visually similar species and makes visual suggestions for how they can be distinguished.
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