Semantic Multimedia Information Retrieval Based on Contextual Descriptions
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Semantic analysis and annotation of textual information with appropriate semantic entities is an essential task to enable content based search on the annotated data. For video resources textual information is rare at first sight. But in recent years the development of technologies for automatic extraction of textual information from audio visual content has advanced. Additionally, video portals allow videos to be annotated with tags and comments by authors as well as users. All this information taken together forms video metadata which is manyfold in various ways. By making use of the characteristics of the different metadata types context can be determined to enable sound and reliable semantic analysis and to support accuracy of understanding the video’s content. This paper proposes a description model of video metadata for semantic analysis taking into account various contextual factors.
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