Google Precision Image Search

New York Times has an article “A Google Prototype for a Precision Image Search” that covers a new research paper (PDF format) from Google, presented at World Wide Web Conference in Beijing, “describing what the researchers call VisualRank, an algorithm for blending image-recognition software methods with techniques for weighting and ranking images that look most […]

New York Times has an article “A Google Prototype for a Precision Image Search” that covers a new research paper (PDF format) from Google, presented at World Wide Web Conference in Beijing, “describing what the researchers call VisualRank, an algorithm for blending image-recognition software methods with techniques for weighting and ranking images that look most similar.”

The research paper, “PageRank for Product Image Search,” is focused on a subset of the images that the giant search engine has cataloged because of the tremendous computing costs required to analyze and compare digital images. To do this for all of the images indexed by the search engine would be impractical, the researchers said. Google does not disclose how many images it has cataloged, but it asserts that its Google Image Search is the “most comprehensive image search on the Web.”

The company said that in its research it had concentrated on the 2000 most popular product queries on Google’s product search, words such as iPod, Xbox and Zune. It then sorted the top 10 images both from its ranking system and the standard Google Image Search results. With a team of 150 Google employees, it created a scoring system for image “relevance.” The researchers said the retrieval returned 83 percent less irrelevant images.

Google is not the first into the visual product search category. Riya, a Silicon Valley start-up, introduced Like.com in 2006. The service, which refers users to shopping sites, makes it possible for a Web shopper to select a particular visual attribute, such as a certain style of brown shoes or a style of buckle, and then be presented with similar products available from competing Web merchants.

The image above comes from the paper and shows examples of images found in a search for [mona lisa]. The lines illustrate how they are all estimated to link together, with the two in the middle (as shown in the close-up below) deemed the most relevant based on linkage:


Google, Search, Image Search, PageRank, Image Rank, Visual Rank, Search Engine