Abstract
Video analysis typically has been pursued in two different directions. Either previous approaches have focused on low-level descriptors, such as dominant color, or they have focused on the video content, such as person or object. In this paper, we present a video analysis environment not only to bridge these two directions but also can extract and manage semantic metadata from multimedia content autonomously for addressing the interaction between browsing and search capabilities. Concretely speaking, we implemented a tool that links MPEG-7 visual descriptors to high-level, domain-specific concepts. Our approach is ontology-driven, in the sense that we provide ontology based domain-specific extensions of the standards for describing the knowledge of video content. In this work, we consider one shot (episode) in the billiard game of video as the specific domain and we will be through the practical works to explain the process of representation of video knowledge. In the experiment part, we prove our approach effectiveness by comparing with the video content retrieval based on only key-word.
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Song, D., Cho, M., Choi, C., Shin, J., Park, J., Kim, P. (2006). Knowledge Representation for Video Assisted by Domain-Specific Ontology. In: Hoffmann, A., Kang, Bh., Richards, D., Tsumoto, S. (eds) Advances in Knowledge Acquisition and Management. PKAW 2006. Lecture Notes in Computer Science(), vol 4303. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11961239_13
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DOI: https://doi.org/10.1007/11961239_13
Publisher Name: Springer, Berlin, Heidelberg
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