A compact, effective descriptor for video copy detection

Mei Chen Yeh*, Kwang Ting Cheng

*Corresponding author for this work

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

33 Citations (Scopus)

Abstract

Large scale video copy detection tasks require a compact and computational-efficient descriptor that is robust to various transformations that are typically applied to generate copies. In this paper, we propose a new frame-level descriptor for such a task. The descriptor encodes the internal structure of a video frame by computing the pair-wise correlations between geometrically pre-indexed blocks. It is conceptually simple, small in size, and fast to compute. Experiments using the MUSCLE VCD benchmark show its superior performance compared to existing approaches.

Original languageEnglish
Title of host publicationMM'09 - Proceedings of the 2009 ACM Multimedia Conference, with Co-located Workshops and Symposiums
Pages633-636
Number of pages4
DOIs
Publication statusPublished - 2009
Externally publishedYes
Event17th ACM International Conference on Multimedia, MM'09, with Co-located Workshops and Symposiums - Beijing, China
Duration: 2009 Oct 192009 Oct 24

Publication series

NameMM'09 - Proceedings of the 2009 ACM Multimedia Conference, with Co-located Workshops and Symposiums

Other

Other17th ACM International Conference on Multimedia, MM'09, with Co-located Workshops and Symposiums
Country/TerritoryChina
CityBeijing
Period2009/10/192009/10/24

Keywords

  • Frame descriptor
  • Graph representation
  • Video copy detection

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Software

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