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ICMCS
2000
IEEE

A Genetic Algorithm for Video Segmentation and Summarization

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A Genetic Algorithm for Video Segmentation and Summarization
We describe a genetic segmentation algorithm for video. This algorithm operates on segments of a string representation. It is similar to both classical genetic algorithms that operate on bits of a string and genetic grouping algorithms that operate on subsets of a set. For evaluating segmentations, we define similarity adjacency functions, which are extremely expensive to optimize with traditional methods. The evolutionary nature of genetic algorithms offers a further advantage by enabling incremental segmentation. Applications include video summarization and indexing for browsing, plus adapting to user access patterns.
Patrick Chiu, Andreas Girgensohn, Wolfgang Polak,
Added 31 Jul 2010
Updated 31 Jul 2010
Type Conference
Year 2000
Where ICMCS
Authors Patrick Chiu, Andreas Girgensohn, Wolfgang Polak, Eleanor G. Rieffel, Lynn Wilcox
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