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Searching by Image Instead of Keywords
Content based image retrieval (CBIR), the technique to search for images not by keywords, but by comparing features of the images themselves has been the focus of much research ever since the web emerged. Consider for instance adding CBIR to Google Images, where you would be able to search for images similar to a query image instead of using keywords. A research project at Penn State University has recently been applied to the biggest aviation photo database in the world with close to 800,000 images. You can search for images similar to a photo already in their database (click "View similar photos") or submit your own query image. Some queries generate better results than others but CBIR is certainly here to stay and will be standard in many image applications of the future.
There's a bunch of interesting papers out there on content-based image analysis and retrieval. Below is a sampling from my bibtex file. Does anyone else have others they'd like to share?
* Finding Naked People (Fleck et al, 1996)
* Video google: A text retrieval approach to object matching in videos (Sivic & Zisserman, 2003): web page demo here
* Names and Faces in the News (Berg et al, 2004)
* FACERET: An Interactive Face Retrieval System Based on Self-Organizing Maps (Ruiz-del-Solar et al, 2002)
* Costume: A New Feature for Automatic Video Content Indexing (Jaffre 2005)
If you are only interested in searching for images on your own computer, have a look at imgSeek. http://imgseek.python-hosting.com/
It's been around for some time now. You can not only use an existing image to search, but also do a rough sketch. Check the screenshots:
Nice complement to what has been presented in this article.
I like my dinosaurs feathery, and my pterosaurs hairy (or is it pycnofibery?)