Object driven semantic multi-video summarisation based on ontology
Article No.: 6, Pages 1 - 6
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Abstract
Multi-Video summarisation frameworks aim to extract representative frames from a collection of videos. In the proposed framework, a multi-video summarisation model is implemented that detects key frames from a collection of related videos on the basis of user query object and ontology inference approach. The framework also develops a novel large-scale ontology for video genre identification based on the characteristics of genre-specific videos. The presence of ontologies aids in generating semantically relevant summaries compared to traditional approaches. Quantitative evaluation ensures that maximum information from the video collection on the basis of query is retrieved. Additionally, the ontology-based query inference approach reduces the computation time significantly. Qualitative results prove that the summary generated is concise, informative and semantically relevant.
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Information & Contributors
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Published In
December 2019
376 pages
ISBN:9781450372848
DOI:10.1145/3368691
- Conference Chair:
- Imad Hoballah,
- Organizing Chair:
- Hassan Zeineddine,
- Program Chairs:
- Shadi A. Aljawarneh,
- Juan. A. Lara
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Association for Computing Machinery
New York, NY, United States
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Published: 02 December 2019
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DATA'19
DATA'19: International Conference on Data Science, E-learning and Information Systems 2019, Sponsored by UAE ACM Chapter
December 2 - 5, 2019
Dubai, United Arab Emirates
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DATA '19 Paper Acceptance Rate 58 of 146 submissions, 40%;
Overall Acceptance Rate 74 of 167 submissions, 44%
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