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Title:
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CONTEXT-BASED IMAGE RETRIEVAL: A CASE STUDY IN BACKGROUND IMAGE ACCESS FOR MULTIMEDIA PRESENTATIONS |
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Author(s):
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Sheng-hao Hung , Pai-hsun Chen , Jen-shin Hong , Samuel Cruz-lara |
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ISBN:
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978-972-8924-44-7 |
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Editors:
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Pedro Isaías , Miguel Baptista Nunes and João Barroso (associate editors Luís Rodrigues and Patrícia Barbosa) |
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Year:
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2007 |
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Edition:
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V II, 2 |
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Keywords:
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Context-based image retrieval, knowledgebase, semantic role labeling, ConceptNet, Multimedia. |
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Type:
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Short Paper |
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First Page:
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158 |
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Last Page:
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162 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Conventional approaches of image indexing and retrieval from digital libraries include content-based, metadata-based,
and keyword-based approaches. This paper addresses a different way of image retrieval motivated by real-life
applications for an intelligent system that can automatically select appropriate background images from textual passages.
We explored techniques for developing automatic image-retrieval systems based on essential contextual information of a
textual passage. We propose a framework that applies semantic role labeling techniques and a commonsense knowledge
base, ConceptNet. The primitive results indicate that the proposed methodology has a potential on applications with
textual passages that describe things and events that are regularly seen in every day life. However, for fantasy tales that
describe truly fictitious things and events, the use of ConceptNet does not allow to obtain accurate results. |
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