Full-reference quality diagnosis for video summary

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 matcThing 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.