VisualRank

VisualRank is a system for finding and ranking images by analysing and comparing their content, rather than searching image names, Web links or other text.

On 1 May 2008 at the International World Wide Web Conference in Beijing, Google scientists Yushi Jing and Shumeet Baluja made their VisualRank work public in a paper: [ [http://www2008.org/papers/pdf/p307-jingA.pdf "PageRank for Product Image Search"] ]

In this paper, we presented a system that used visual cues, instead of solely text information, to determine the rank of images. The idea was simple: find common visual themes in a set of images, and then find a small set of images that best represented those themes. The resulting algorithm wound up being PageRank, but on an entirely inferred graph of image similarities.

References

External links

* [http://www.nytimes.com/2008/04/28/technology/28google.html?adxnnl=1&ref=business&adxnnlx=1210140241-DOwaJr/5AjMPCYJDerw++Q New York Times article]
* [http://tech.slashdot.org/article.pl?sid=08/04/28/1852254&from=rss Slashdot article]