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CLEF
2008
Springer

Exploiting Term Co-occurrence for Enhancing Automated Image Annotation

11 years 7 months ago
Exploiting Term Co-occurrence for Enhancing Automated Image Annotation
This paper describes an application of statistical co-occurrence techniques that built on top of a probabilistic image annotation framework is able to increase the precision of an image annotation system. We observe that probabilistic image analysis by itself is not enough to describe the rich semantics of an image. Our hypothesis is that more accurate annotations can be produced by introducing additional knowledge in the form of statistical co-occurrence of terms. This is provided by the context of images that otherwise independent keyword generation would miss. We applied our algorithm to the dataset provided by ImageCLEF 2008 for the Visual Concept Detection Task (VCDT). Our algorithm not only obtained better results but also it appeared in the top quartile of all methods submitted in ImageCLEF 2008.
Ainhoa Llorente, Simon E. Overell, Haiming Liu 000
Added 18 Oct 2010
Updated 18 Oct 2010
Type Conference
Year 2008
Where CLEF
Authors Ainhoa Llorente, Simon E. Overell, Haiming Liu 0002, Rui Hu, Adam Rae, Jianhan Zhu, Dawei Song, Stefan M. Rüger
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