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On Linked Open Data (LOD)-based Semantic Video Annotation Systems

Author(s)
Mu mtaz Kh an Department of Computer Science, University of Peshawar,Peshawar,Pakistan
Sh ah Kh usro Department of Computer Science, University of Peshawar,Peshawar,Pakistan
Irfan Ullah Department of Computer Science, University of Peshawar,Peshawar,Pakistan
Abstract
The advent of Web 2.0 and the rapid growth of video annotation systems have resulted in huge multimedia repositories where multimedia has become among the primary contents that are available on the Web. Annotating videos enable users in easily searching and retrieving multimedia contents on the Web. This practice also enables these systems to share multimedia contents as well. Annotations, if used properly, could be among the key factors in improving search efficiency, interoperability, video indexing and multimedia content analysis. However, user-generated annotations for multimedia content still remain inaccessible to the web of data. The available video-annotation systems provide format-dependent annotations in a proprietary manner. In addition, these annotations are just used within a single system and often cannot be reused, shared, linked, and explored by other communities. This paper aims at video searching problems in different traditional and currently available video-sharing web applications with their annotation tools and their limitations and shortcomings. In addition, this paper focuses on pointing out video searching problem in different ontology-based video-sharing web applications and video annotation systems. We are also investigating the distinguishing features of different LOD-based video-sharing web applications and LOD-based video annotation systems as well as focusing on new research trends to make it an access point for further readings.
Publication Details
Page(s) 1-12
DOI DOI not available
Published Journal: Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences, Volume: 54, Issue: 1, Year: 2017

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Keywords
ontology, linked open data (LOD), annotations, semantic video annotation systems, video annotation, Multimedia
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