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- W4235137931 abstract "This paper introduces a complete framework for temporal video segmentation. First, a computationally efficient shot extraction method is introduced, which adopts the normalized graph partition approach, enriched with a non-linear, multiresolution filtering of the similarity vectors involved. The shot boundary detection technique proposed yields high precision (90%) and recall (95%) rates, for all types of transitions, both abrupt and gradual. Next, for each detected shot, the authors construct a static storyboard by introducing a leap keyframe extraction method. The video abstraction algorithm is 23% faster than existing techniques for similar performances. Finally, the authors propose a shot grouping strategy that iteratively clusters visually similar shots under a set of temporal constraints. Two different types of visual features are exploited: HSV color histograms and interest points. In both cases, the precision and recall rates present average performances of 86%." @default.
- W4235137931 created "2022-05-12" @default.
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- W4235137931 date "2013-01-01" @default.
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- W4235137931 title "Video Segmentation and Structuring for Indexing Applications" @default.
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- W4235137931 doi "https://doi.org/10.4018/978-1-4666-2940-0.ch011" @default.
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