Please use this identifier to cite or link to this item:
https://doi.org/10.1109/TCSVT.2010.2077531
Title: | Efficient mining of multiple partial near-duplicate alignments by temporal network |
Authors: | Tan, H.-K. Ngo, C.-W. Chua, T.-S. |
Keywords: | Keyword matching partial near-duplicate temporal graph |
Issue Date: | 2010 |
Citation: | Tan, H.-K., Ngo, C.-W., Chua, T.-S. (2010). Efficient mining of multiple partial near-duplicate alignments by temporal network. IEEE Transactions on Circuits and Systems for Video Technology 20 (11) : 1486-1498. ScholarBank@NUS Repository. https://doi.org/10.1109/TCSVT.2010.2077531 |
Abstract: | This paper considers the mining and localization of near-duplicate segments at arbitrary positions of partial near-duplicate videos in a corpus. Temporal network is proposed to model the visual-temporal consistency between video sequence by embedding temporal constraints as directed edges in the network. Partial alignment is then achieved through network flow programming. To handle multiple alignments, we consider two properties of network structure: conciseness and divisibility, to ensure that the mining is efficient and effective. Frame-level matching is further integrated in the temporal network for alignment verification. This results in an iterative alignment-verification procedure to fine tune the localization of near-duplicate segments. The scalability of frame-level matching is enhanced by exploring visual keyword matching algorithms. We demonstrate the proposed work for mining partial alignments from two months of broadcast videos and across six TV sources. © 2006 IEEE. |
Source Title: | IEEE Transactions on Circuits and Systems for Video Technology |
URI: | http://scholarbank.nus.edu.sg/handle/10635/39891 |
ISSN: | 10518215 |
DOI: | 10.1109/TCSVT.2010.2077531 |
Appears in Collections: | Staff Publications |
Show full item record
Files in This Item:
There are no files associated with this item.
SCOPUSTM
Citations
12
checked on Feb 15, 2019
WEB OF SCIENCETM
Citations
10
checked on Feb 6, 2019
Page view(s)
96
checked on Feb 9, 2019
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.