DocumentCode :
2428699
Title :
Time-constrained clustering for segmentation of video into story units
Author :
Yeung, Minerva M. ; Boon-Lock Yeo
Author_Institution :
Dept. of Electr. Eng., Princeton Univ., NJ, USA
Volume :
3
fYear :
1996
fDate :
25-29 Aug 1996
Firstpage :
375
Abstract :
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
Keywords :
feature extraction; graph theory; image segmentation; video signal processing; visual databases; scene segmentation; scene transition graph; story unit extraction; temporal locality; time-constrained clustering; video browsing; video content clustering; video database; video documents; visual similarity; Gunshot detection systems; Image analysis; Image color analysis; Image databases; Image motion analysis; Layout; Motion pictures; Navigation; Video sequences; Visual databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
ISSN :
1051-4651
Print_ISBN :
0-8186-7282-X
Type :
conf
DOI :
10.1109/ICPR.1996.546973
Filename :
546973
Link To Document :
بازگشت