New image recognition webapp ALIPR (Automatic Linguistic Indexing of Pictures in Real-Time) is a on a mission to assign relevant tags to digital images based on their content, and wants you to help it learn. While digital image recognition has come a long way in recent years, it's still got a long way to go, and ALIPR's got its share of hits and misses. Upload an image to ALIPR or hand it a URL of an image already online, and the engine will suggest tags, and ask you to add to its list. Some of ALIPR's suggestions are spot-on, but others are way off. You can confirm the hits and suggest other tags to help the engine learn. Check out how ALIPR did with a few images from my Flickr photostream.
Given a photos of boats in the harbor and a skyline, ALIPR does pretty well with its tag suggestions:
But a clear photo of a spider doesn't net any tags that apply:
Given a more confusing photo of a rock sculpture outside a building, ALIPR identifies the sky and buildings:
But a clear photo of a fire only returns the "orange" tag, not the word fire:
The concept of ALIPR is super exciting for anyone who's building a library of digital photos, because the most tedious parts of organising and searching your photos is adding relevant keywords to them. So automatic photo tagging, when done well and accurately, could be a huge time saver. Can't wait to see ALIPR-like technology built-in to a desktop photo organizer like Picasa. In the meantime, you can also use ALIPR's growing library of tagged photos to search for images by keyword as well.