Abstract
This paper presents a prototype system that helps users manage and search collections of their digital photos. Existing systems and methods suffer from some shortcomings. For example, the visual similarity based search has poor precision and lacks for semantic information, while the text-based retrieval is only lexically motivated and those lexicons are not organized well. In one word, systems that really support intelligent retrieval are rare. In order to overcome these shortcomings, an ontology based approach is proposed for photo management, which is conceptual motivated. The approach is implemented in the OntoAlbum system. When a photo is imported into the database, the system automatically creates an instance of it. Then the user annotates the photo with concepts of ontology. Finally, by clicking on an instance of concepts in the ontology, the user can find all the photos related to the instance through ontology inference. Ontology provides a formal, explicit and conceptual annotation as well as an effective inference query. It makes intelligent retrieval possible in the photo management system. Experiments on the OntoAlbum system show that the proposed approach is very effective and promising.
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Chai, YM., Zhu, XY., Jia, JP. (2008). OntoAlbum: An Ontology Based Digital Photo Management System. In: Campilho, A., Kamel, M. (eds) Image Analysis and Recognition. ICIAR 2008. Lecture Notes in Computer Science, vol 5112. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69812-8_26
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DOI: https://doi.org/10.1007/978-3-540-69812-8_26
Publisher Name: Springer, Berlin, Heidelberg
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