P.L. has a great summary of a Slashdot post concerning content based image retrieval (CBIR) and research from Penn St. University.
?CBIR? is the handy acronym for Content based image retrieval. Basically, it means instead of entering text to find images, you provide or click on an existing image to find related ones. This ought to be much more intuitive for certain tasks.
A CBIR research project of Penn State University has now been applied to an aviation images database, Slashdot reports. Click on ?Show me photos?, and then click on ?View similar photos? to get an idea of how well this works. This is not necessary related to actual image recognition (analyzing a picture to find out it contains, say, an elephant), but can be implemented using much more brute force pixel-by-pixel image comparison with some added mirror and scaling fuzzyness.
I was hoping to share another CBIR demo caled Image-Seek from LTU Technologies. It allowed you to search and find similar photos from a collection of Corbis images. However, according to the LTU site it's "temporarily unavailable." Oh well, you can still read about it.
Also, LTU presentations from the 2003 and 2004 Search Engine Meeting provide excellent intros to CBIR:
+ Organising personal pictures with content analysis technology
From the 2004 meeting. PDF file.
+ Finding the Right Image in the Corbis Collection
From the 2003 meeting. PDF file.
Meet Your Favorite Search Engine Watch Contributors
Many of SEW's leading expert contributors will be at ClickZ Live, the new online and digital marketing event kicking off in New York (March 31-April 3). Hear from the likes of: Thom Craver, Josh Braaten, Lisa Barone, Simon Heseltine, Josh McCoy, Lisa Raehsler, Greg Jarboe, Dan Cristo, Joseph Kerschbaum, John Gagnon, Eric Enge and more!