Today at the 
Google says it has managed to achieve 80% accuracy on over 50,000 landmarks. Google demonstrated how it did this with the Acropolis. Essentially, they began with an unnamed, untagged picture of it, entered the web address into the recognition engine, and the computer identified it as "Recognized Landmark: Acropolis, Athens, Greece."
To make a long and technical story short, Google generated a list of landmarks based on GPS-tagged photos from Picasa and Panoramio, and online tour guide webpages. Google then found "candidate images" for each landmark using those resources as well as Google Image Search. These images were "pruned using efficient image matching and unsupervised clustering techniques, as Yagnik explains. Then Google developed an indexing system for fast image recognition.
There isn't really any mention of how such an engine could contribute to the improvement of Google Image Search in the research paper, but given that search, and "organizing the world's information" are what Google is essentially all about, it's not hard to imagine this technology being incorporated into how Google retrieves results for Image Search in the future.
No comments yet. Be the first to comment!