Time-constrained clustering for segmentation of video into story units

Many video programs have story structures that can be recognized through the clustering of video contents based on low-level visual primitives, and the analysis of high level structures imposed by temporal arrangement of composing elements. In this paper time-constrained clustering of video shots is...

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Bibliographic Details
Published inProceedings of 13th International Conference on Pattern Recognition Vol. 3; pp. 375 - 380 vol.3
Main Authors Yeung, M.M., Boon-Lock Yeo
Format Conference Proceeding
LanguageEnglish
Published IEEE 1996
Subjects
Gunshot detection systems
Image analysis
Image color analysis
Image databases
Image motion analysis
Layout
Motion pictures
Navigation
Video sequences
Visual databases
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Summary:Many video programs have story structures that can be recognized through the clustering of video contents based on low-level visual primitives, and the analysis of high level structures imposed by temporal arrangement of composing elements. In this paper time-constrained clustering of video shots is proposed to collapse visually similar and temporally local shots into a compact structure. We show that the proposed clustering formulations, when incorporated into the scene transition graph framework, allows the automatic segmentation of scenes and story units that cannot be achieved by existing shot boundary detection schemes. The proposed method is able to decompose video into meaningful hierarchies and provide compact representations that reflect the flow of story, thus offering efficient browsing and organization of video.
ISBN:9780818672828
081867282X
ISSN:1051-4651
DOI:10.1109/ICPR.1996.546973