Full-reference quality diagnosis for video summary

Yan Liu, Yan Zhang, Maosong Sun, Wenjie Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)


As video summarization techniques have attracted more and more attention for efficient multimedia data management, objective quality assessment of video summary is desired. To address the lack of automatic evaluation techniques, this paper proposes a 3C-Diagnosis algorithm to diagnose the video summary from the perspective of coverage, conciseness, and coherence. The candidate summary is first aligned against the reference summary. Then the coverage of the candidate summary is calculated according to the information bearing of the matching frames and the information loss of the missing frames. The conciseness is calculated based on the unwanted information contained in the candidate summary, and the coherence is calculated based on the ratio of the appearances of the frame loss for the aligned candidate summary. The proposed techniques are experimented on a standard dataset of TRECVID 2007 and show good performance.
Original languageEnglish
Title of host publication2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Proceedings
Number of pages4
Publication statusPublished - 23 Oct 2008
Event2008 IEEE International Conference on Multimedia and Expo, ICME 2008 - Hannover, Germany
Duration: 23 Jun 200826 Jun 2008


Conference2008 IEEE International Conference on Multimedia and Expo, ICME 2008


  • Full-reference assessment
  • Quality diagnosis
  • Video summarization

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering


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