A team of researchers led by computer scientist Serge Belongie at the University of California, San Diego, has good news for birders: they have developed an iPad app that will identify most North American birds, with a little help from a human user.
The app is essentially an interactive field guide, where computer vision algorithms analyze the picture the user submitted, ask questions and call up pages with pictures and information about a bird species that is a likely match. The researchers' ultimate goal is to fill a gap in the world of online search. Text-driven search, such as Google and Wikipedia, has been wildly successful. But identifying images has so far proven much more difficult.
That process involves uploading a picture to a search tool, such as Google Goggles, and asking what it is. This works well with well-known landmarks and pictures. But it mostly fails with lesser-known visuals, such as images of animals and plants.
Computer scientists at the Jacobs School of Engineering at UC San Diego, UC Berkeley and Caltech have designed a search system that can interact with users to provide more accurate results. For example, when the system is stumped, users can label parts of an image, such as a bird's head, chest and tail and provide information about other characteristics, such as the color of the bird's coat.
"We chose birds for several reasons: there is an abundance of excellent photos of birds available on the Internet, the diversity in appearance across different bird species presents a deep technical challenge and, perhaps most importantly, there is a large community of passionate birders who can put our system to the test," explained Belongie, the Jacobs School of Engineering computer scientist at the heart of the project.
The Cornell Lab of Ornithology is contributing its database of images showing the male, female and juveniles of more than 500 North American species. Citizen scientists working with the laboratory
|Contact: Ioana Patringenaru|
University of California - San Diego