From pixels to semantic spaces: Advances in content-based image retrieval

Technological advances in digital imaging, broadband networking, and data storage are motivating millions of people to communicate with one another and express themselves by sharing images, video, and other forms of media online. Acquiring, storing, and transmitting photos is now trivial, but to manipulate, index, sort, filter, summarize, or search through them is significantly harder. The Statistical Visual Computing Laboratory at the University of California, San Diego, has been considering the problem of content-based image retrieval for years. This effort explores many issues in image representation and intelligent system design, including the evaluation of image similarity, automatic annotation of images with descriptive captions, and the ability to understand user feedback during image search.