Video Segmentation and Structuring for Indexing Applications

Ruxandra Tapu and Titus Zaharia
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Ruxandra Tapu: TELECOM SudParis, France
Titus Zaharia: TELECOM SudParis, France

International Journal of Multimedia Data Engineering and Management (IJMDEM), 2011, vol. 2, issue 4, 38-58

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%.

Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jmdem0:v:2:y:2011:i:4:p:38-58

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International Journal of Multimedia Data Engineering and Management (IJMDEM) is currently edited by Shu-Ching Chen

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