Visual Concept Ontology for Image Annotations
Jan Botorek, Petra Budikova, Pavel Zezula

TL;DR
This paper introduces the Visual Concept Ontology (VCO), a structured semantic resource linked with WordNet, designed to improve general-purpose image annotation by providing organized visual concepts for multimedia retrieval.
Contribution
The paper presents a novel ontology of visual concepts (VCO) integrated with WordNet, enhancing automatic image annotation and multimedia search capabilities.
Findings
VCO improves image annotation accuracy.
Linked with WordNet for richer semantic information.
Facilitates better multimedia retrieval.
Abstract
In spite of the development of content-based data management, text-based searching remains the primary means of multimedia retrieval in many areas. Automatic creation of text metadata is thus a crucial tool for increasing the findability of multimedia objects. Search-based annotation tools try to provide content-descriptive keywords by exploiting web data, which are easily available but unstructured and noisy. Such data need to be analyzed with the help of semantic resources that provide knowledge about objects and relationships in a given domain. In this paper, we focus on the task of general-purpose image annotation and present the VCO, a new ontology of visual concepts developed as a part of image annotation framework. The ontology is linked with the WordNet lexical database, so the annotation tools can easily integrate information from both these resources.
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Taxonomy
TopicsImage Retrieval and Classification Techniques · Advanced Image and Video Retrieval Techniques · Biomedical Text Mining and Ontologies
