Image interpretation using large corpus: Wikipedia
|Image interpretation using large corpus: Wikipedia|
|Author(s)||Rahurkar M., Tsai S.-F., Dagli C., Huang T.S.|
|Published in||Proceedings of the IEEE|
|Keyword(s)||Concepts, Image understanding, Wikipedia (Extra: Human knowledge, Image interpretation, Image representations, Link structure, Semantic concept, Semantic content, Use concept, Wikipedia, World knowledge, Computer vision, Image analysis, Image understanding, Semantics, Knowledge representation)|
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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.
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