Google outlines vision for better image search

Google thinks it has made a breakthrough in 'computer vision'.

Imagine that you're searching for holiday destinations online and you stumble upon a picture of a beautiful site in Europe that you don't recognise, filled with ancient ruins. Google has developed a way to let a user provide Google with the URL for that image and search a database of over 40 million geotagged photos to match that image to verified landmarks. Then you've got a destination for your next trip.

To create the 'landmark recognition engine', Google took advantage of the 40 million or so images in Picasa and Panoromio that are geotagged with the locations of famous landmarks, like the Eiffel Tower. It also assembled images from travel guide sites such as Wikitravel, providing a base of landmark photos that have been verified by experts.

With all that data as a backdrop, researchers figured out a way to find the most representative pictures of a landmark using a clustering technique to group images taken from similar perspectives, as well as toss out 'noisy' images, such as a picture of your family on the street in front of the Eiffel Tower, that don't really show the landmark.

Then, when given a fresh image to analyse, the system uses pixel-matching techniques to find small patterns within that image and look for similar patterns within verified photos of landmarks. Google said the system has been able to return an accurate result 80 per cent of the time, not only naming the landmark but suppling additional information about the place too.

Google is by no means certain when, or if, this research will turn into a product. It is excited, however, that it has found a way to use computers to process large sets of data available on the Internet and return accurate information about images. Doing this with text, of course, is what has made Google Google.