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2007
Springer

Automatic Image Annotation Using a Visual Dictionary Based on Reliable Image Segmentation

10 years 1 months ago
Automatic Image Annotation Using a Visual Dictionary Based on Reliable Image Segmentation
Recent approaches in Automatic Image Annotation (AIA) try to combine the expressiveness of natural language queries with approaches to minimize the manual effort for image annotation. The main idea is to infer the annotations of unseen images using a small set of manually annotated training examples. However, typically these approaches suffer from low correlation between the globally assigned annotations and the local features used to obtain annotations automatically. In this paper we propose a framework to support image annotations based on a visual dictionary that is created automatically using a set of locally annotated training images. We designed a segmentation and annotation interface to allow for easy annotation of the traing data. In order to provide a framework that is easily extendable and reusable we make broad use of the MPEG-7 standard.
Christian Hentschel, Sebastian Stober, Andreas N&u
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where AMR
Authors Christian Hentschel, Sebastian Stober, Andreas Nürnberger, Marcin Detyniecki
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