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.

Google Google LLC () is an American multinational technology company focusing on search engine technology, online advertising, cloud computing, computer software, quantum computing, e-commerce, artificial intelligence, and consumer electronics. I ...

scientists made their VisualRank work public in a paper describing applying

PageRank PageRank (PR) is an algorithm used by Google Search to rank web pages in their search engine results. It is named after both the term "web page" and co-founder Larry Page. PageRank is a way of measuring the importance of website pages. According ...

to Google image search at the International World Wide Web Conference in

Beijing } Beijing ( ; ; ), alternatively romanized as Peking ( ), is the capital of the People's Republic of China. It is the center of power and development of the country. Beijing is the world's most populous national capital city, with over 2 ...

in 2008. .

Methods

Both

computer vision Computer vision is an interdisciplinary scientific field that deals with how computers can gain high-level understanding from digital images or videos. From the perspective of engineering, it seeks to understand and automate tasks that the human ...

techniques and

locality-sensitive hashing In computer science, locality-sensitive hashing (LSH) is an algorithmic technique that hashes similar input items into the same "buckets" with high probability. (The number of buckets is much smaller than the universe of possible input items.) Sinc ...

(LSH) are used in the VisualRank

algorithm In mathematics and computer science, an algorithm () is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation. Algorithms are used as specifications for performing ...

. Consider an image search initiated by a text query. An existing search technique based on image metadata and surrounding text is used to retrieve the initial result candidates (

), which along with other images in the index are clustered in a

graph Graph may refer to: Mathematics *Graph (discrete mathematics), a structure made of vertices and edges **Graph theory, the study of such graphs and their properties * Graph (topology), a topological space resembling a graph in the sense of discr ...

according to their similarity (which is precomputed). Centrality is then measured on the clustering, which will return the most canonical image(s) with respect to the query. The idea here is that agreement between users of the web about the image and its related concepts will result in those images being deemed more similar. VisualRank is defined iteratively by

VR = S^* \times VR

, where

S^*

is the image similarity matrix. As matrices are used,

eigenvector centrality In graph theory, eigenvector centrality (also called eigencentrality or prestige score) is a measure of the influence of a node in a network. Relative scores are assigned to all nodes in the network based on the concept that connections to high-sco ...

will be the measure applied, with repeated multiplication of

VR

and

S^*

producing the

eigenvector In linear algebra, an eigenvector () or characteristic vector of a linear transformation is a nonzero vector that changes at most by a scalar factor when that linear transformation is applied to it. The corresponding eigenvalue, often denoted b ...

we're looking for. Clearly, the image similarity measure is crucial to the performance of VisualRank since it determines the underlying graph structure. The main VisualRank system begins with local feature vectors being extracted from images using

scale-invariant feature transform The scale-invariant feature transform (SIFT) is a computer vision algorithm to detect, describe, and match local ''features'' in images, invented by David Lowe in 1999. Applications include object recognition, robotic mapping and navigation, ima ...

(SIFT). Local feature descriptors are used instead of color histograms as they allow similarity to be considered between images with potential rotation, scale, and perspective transformations. Locality-sensitive hashing is then applied to these feature vectors using the p-stable distribution scheme. In addition to this, LSH amplification using AND/OR constructions are applied. As part of the applied scheme, a

Gaussian distribution In statistics, a normal distribution or Gaussian distribution is a type of continuous probability distribution for a real-valued random variable. The general form of its probability density function is : f(x) = \frac e^ The parameter \mu ...

is used under the

\ell_2

norm.

References

{{Reflist

External links

New York Times articleSlashdot article
Internet search Image processing