Image interpretation using large corpus: Wikipedia

Mandar Rahurkar, Shen Fu Tsai, Charlie Dagli, Thomas S. Huang

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


Image is a powerful medium for expressing one's ideas and rightly confirms the adage, One picture is worth a thousand words. In this work, we explore the application of world knowledge in the form of Wikipedia to achieve this objectiveliterally. In the first part, we disambiguate and rank semantic concepts associated with ambiguous keywords by exploiting link structure of articles in Wikipedia. In the second part, we explore an image representation in terms of keywords which reflect the semantic content of an image. Our approach is inspired by the desire to augment low-level image representation with massive amounts of world knowledge, to facilitate computer vision tasks like image retrieval based on this information. We represent an image as a weighted mixture of a predetermined set of concrete concepts whose definition has been agreed upon by a wide variety of audience. To achieve this objective, we use concepts defined by Wikipedia articles, e.g., sky, building, or automobile. An important advantage of our approach is availability of vast amounts of highly organized human knowledge in Wikipedia. Wikipedia evolves rapidly steadily increasing its breadth and depth over time.

Original languageEnglish
Article number5484723
Pages (from-to)1509-1525
Number of pages17
JournalProceedings of the IEEE
Issue number8
StatePublished - Aug 2010


  • Concepts
  • Image understanding
  • Wikipedia


Dive into the research topics of 'Image interpretation using large corpus: Wikipedia'. Together they form a unique fingerprint.

Cite this