Practical online near-duplicate subsequence detection for continuous video streams

Huang, Zi, Shen, Heng Tao, Shao, Jie, Cui, Bin and Zhou, Xiaofang (2010) Practical online near-duplicate subsequence detection for continuous video streams. IEEE Transactions on Multimedia, 12 5: 386-398. doi:10.1109/TMM.2010.2050737

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Author Huang, Zi
Shen, Heng Tao
Shao, Jie
Cui, Bin
Zhou, Xiaofang
Title Practical online near-duplicate subsequence detection for continuous video streams
Journal name IEEE Transactions on Multimedia   Check publisher's open access policy
ISSN 1520-9210
Publication date 2010-08
Year available 2011
Sub-type Article (original research)
DOI 10.1109/TMM.2010.2050737
Volume 12
Issue 5
Start page 386
End page 398
Total pages 13
Place of publication Piscataway, NJ, United States
Publisher Institute of Electrical and Electronics Engineers
Collection year 2011
Language eng
Subject 0803 Computer Software
0906 Electrical and Electronic Engineering
Abstract Online video content is surging to an unprecedented level. Massive video publishing and sharing impose heavy demands on online near-duplicate detection for many novel video applications. This paper presents an accurate and practical system for online near-duplicate subsequence detection over continuous video streams. We propose to transform a video stream into a one-dimensional video distance trajectory (VDT) monitoring the continuous changes of consecutive frames with respect to a reference point, which is further segmented and represented by a sequence of compact signatures called linear smoothing functions (LSFs). LSFs of each subsequence of the incoming video stream are continuously generated and temporally stored in a buffer for comparison with query LSFs. LSF adopts compound probability to combine three independent video factors for effective segment similarity measure, which is then utilized to compute sequence similarity for near-duplicate detection. To avoid unnecessary sequence similarity computations, an efficient sequence skipping strategy is also embedded. Experimental results on detecting diverse near-duplicates of TV commercials in real video streams show the superior performance of our system on both effectiveness and efficiency over existing methods.
Keyword Continuous detection
Near-duplicate subsequence
Online detection
Subsequence match
Video stream
Quick search method
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2011 Collection
School of Information Technology and Electrical Engineering Publications
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Citation counts: TR Web of Science Citation Count  Cited 16 times in Thomson Reuters Web of Science Article | Citations
Scopus Citation Count Cited 24 times in Scopus Article | Citations
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Created: Sun, 17 Oct 2010, 00:10:55 EST