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Title of Journal: Vis Comput

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Abbravation: The Visual Computer

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Springer Berlin Heidelberg

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DOI

10.1016/0006-8993(84)90693-0

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1432-2315

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A bagofsemantics model for image clustering

Authors: Na Chen Viktor K Prasanna
Publish Date: 2013/03/09
Volume: 29, Issue: 11, Pages: 1221-1229
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Abstract

This paper presents a novel method to organize a collection of images into a hierarchy of clusters based on image semantics Given a group of raw images with no metadata as input our method describes the semantics of each image with a bagofsemantics model ie a set of meaningful descriptors which is derived from the image’s Object Relation Network Chen et al in Proceedings of the 21st International Conference on World Wide Web 2012—an expressive graph model representing rich semantics for image objects and their relations We adopt the class hierarchies in a guide ontology as different levels of lenses to view the bagofsemantics models Image clusters are automatically extracted by grouping images with the same bagofsemantics viewed through a certain lens With a series of coarsetofine lenses images are clustered in a topdown hierarchical manner In addition given that users can have different perspectives regarding how images should be clustered our method allows each user to control the clustering process while browsing and thus dynamically adjusts the clustering result according to the user’s preferences

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