Case of Culture: Using Multimedia Ontologies for Automatic Image Annotation and Classification

Authors: Rinaldi, A.M. ; Dipt. di Ing. Elettr. e delle Tecnol. dell'Inf., Univ. di Napoli Federico II, Naples, Italy

Abstract: In the era of big data, the use of formal models and techniques to represent and manage information is a necessary task to implement efficient intelligent information systems. In this paper we propose a complete framework to annotate and categorize images. Our approach is based on multimedia ontologies organized following a formal model to represent knowledge. Our ontologies use multimedia data and linguistic properties to bridge the gap between the target semantic classes and the available low-level multimedia descriptors. The multimedia features are automatically extracted using algorithms based on MPEG-7 standard. The informative image content is annotated with semantic information extracted from our ontologies and the categories are dynamically built by means of a general knowledge base. Experimental results show the efficiency of our approach in the annotation and classification tasks using a combination of textual and visual components.

Published in: Big Data (BigData Congress), 2014 IEEE International Congress on

Date of Conference: June 27 2014-July 2 2014