DocumentCode :
3268994
Title :
Multi-video summarization based on AV-MMR
Author :
Li, Yingbo ; Merialdo, Bernard
Author_Institution :
Inst. Eurecom, Sophia-Antipolis, France
fYear :
2010
fDate :
23-25 June 2010
Firstpage :
1
Lastpage :
6
Abstract :
This paper presents an algorithm for video summarization, Audio Video Maximal Marginal Relevance (AV-MMR), exploiting both audio and video information. It is an extension of the Video Maximal Marginal Relevance (Video-MMR) algorithm which was only based on visual information. AV-MMR iteratively selects segments which best represent unselected information and are non redundant with previously selected information. As for Video-MMR, AV-MMR is a generic algorithm which is suitable for both single and multiple videos with multiple genres. Several variants of AV-MMR are proposed and the best one is identified by experimentation. Besides, a visual representation of the coherence of audio and video information for a set of audio-visual sequences is also proposed.
Keywords :
video databases; AV-MMR algorithm; audio information; audio video maximal marginal relevance; multivideo summarization; video information; Audio recording; Digital recording; Iterative algorithms; MPEG 7 Standard; Motion analysis; Motion pictures; TV; Video recording; Video sequences; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Content-Based Multimedia Indexing (CBMI), 2010 International Workshop on
Conference_Location :
Grenoble
ISSN :
1949-3983
Print_ISBN :
978-1-4244-8028-9
Electronic_ISBN :
1949-3983
Type :
conf
DOI :
10.1109/CBMI.2010.5529899
Filename :
5529899
Link To Document :
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