Near-duplicate subsequence matching for video streams

Chih Yi Chiu, Yi Cheng Jhuang, Guei Wun Han, Li Wei Kang*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this paper, we study the efficiency problem of near-duplicate subsequence matching for video streams. A simple but effective algorithm called incremental similarity update is proposed to address the problem. A similarity upper bound between two videos can be calculated incrementally by taking a lightweight computation to filter out the unnecessary time-consuming computation for the actual similarity between two videos. We integrate the algorithm with inverted frame indexing to scan video sequences for matching near-duplicate subsequences. Four state-of-the-art methods are implemented for comparison in terms of the accuracy, execution time, and memory consumption. Experimental results demonstrate the proposed algorithm yields comparable accuracy, compact memory size, and more efficient execution time.

Original languageEnglish
Title of host publication2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013
DOIs
Publication statusPublished - 2013
Externally publishedYes
Event2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013 - Kaohsiung, Taiwan
Duration: 2013 Oct 292013 Nov 1

Publication series

Name2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013

Conference

Conference2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA 2013
Country/TerritoryTaiwan
CityKaohsiung
Period2013/10/292013/11/01

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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