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Annotating Image Regions Using Spatial Context

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4 Author(s)
Zhiyong Wang ; Sch. of Inf. Technol., Sydney Univ., NSW ; Feng, D.D. ; Zheru Chi ; Tian Xia

Image annotation plays an important role in bridging the semantic gap between low level features and high level semantic contents in image access. In this paper, such a task is tackled by annotating regions which are primitives of a visual scene. We propose a probabilistic model to characterize spatial context for region annotation. Such a model provides a unifying framework integrating both feature distribution models and spatial context models. A wide range of advanced modeling techniques can be utilized to further extend this framework. The approach is also potentially scalable to a large number of semantic concepts and a large number of images. Experimental results based on simple parametric models demonstrate promising results of our approach by investigating the impacts of neighbors, segmentation, and visual features

Published in:

Multimedia, 2006. ISM'06. Eighth IEEE International Symposium on

Date of Conference:

Dec. 2006