The CPR model for summarizing video
MMDB 2003: Proceedings of the First ACM International Workshop on Multimedia Databases, Page: 2-9
2003
- 10Citations
- 3Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
Most past work on video summarization has been based on selecting key frames from videos. We propose a model of video summarization based on three important parameters: Priority (of frames), Continuity (of the summary), and non-Repetition (of the summary). In short, a summary must include high priority frames, must be continuous and non-repetitive. An optimal summary is one that maximizes an objective function based on these three parameters. We develop formal definitions of all these concepts and provide algorithms to find optimal summaries. We briefly report on the performance of these algorithms. Copyright 2003 ACM.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=18844433530&origin=inward; http://dx.doi.org/10.1145/951678.951679; http://portal.acm.org/citation.cfm?doid=951676.951679; https://dl.acm.org/doi/10.1145/951676.951679; http://dx.doi.org/10.1145/951676.951679; https://dx.doi.org/10.1145/951678.951679
Association for Computing Machinery (ACM)
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