Abstract
Language | English |
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Title of host publication | TVS'08 Proc. of the 2nd ACM TRECVID Video Summarisation Workshop |
Pages | 26-30 |
Number of pages | 5 |
DOIs | |
Publication status | Published - 2008 |
Event | TRECVid 2008 - , United Kingdom Duration: 1 Feb 2008 → … |
Conference
Conference | TRECVid 2008 |
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Country | United Kingdom |
Period | 1/02/08 → … |
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Keywords
- adaptive clustering
- hierarchical modelling
Cite this
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Hierarchical modeling and adaptive clustering for real-time summarization of rush videos in TRECVID’08. / Ren, Jinchang; Jiang , J.; Eckes, Christian.
TVS'08 Proc. of the 2nd ACM TRECVID Video Summarisation Workshop. 2008. p. 26-30.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book
TY - GEN
T1 - Hierarchical modeling and adaptive clustering for real-time summarization of rush videos in TRECVID’08
AU - Ren, Jinchang
AU - Jiang , J.
AU - Eckes, Christian
PY - 2008
Y1 - 2008
N2 - In this paper, our techniques used in TRECVID'08 on BBC rush summarization are described. Firstly, rush videos are hierarchical modeled using formal language description. Then, shot detection and V-unit determination are applied for video structuring; junk frames within the model are also effectively removed. Thirdly, adaptive clustering is employed to group shots into clusters to remove retakes. Then, each selected shot is ranked according to its length and sum of activity level for summarization. Competitive results have proved the effectiveness and efficiency of our techniques fully implemented in compressed-domain.
AB - In this paper, our techniques used in TRECVID'08 on BBC rush summarization are described. Firstly, rush videos are hierarchical modeled using formal language description. Then, shot detection and V-unit determination are applied for video structuring; junk frames within the model are also effectively removed. Thirdly, adaptive clustering is employed to group shots into clusters to remove retakes. Then, each selected shot is ranked according to its length and sum of activity level for summarization. Competitive results have proved the effectiveness and efficiency of our techniques fully implemented in compressed-domain.
KW - adaptive clustering
KW - hierarchical modelling
U2 - 10.1145/1463563.1463566
DO - 10.1145/1463563.1463566
M3 - Conference contribution book
SN - 978-1-60558-309-9
SP - 26
EP - 30
BT - TVS'08 Proc. of the 2nd ACM TRECVID Video Summarisation Workshop
ER -