DocumentCode :
2580684
Title :
Multi-video summarization based on OB-MMR
Author :
Li, Yingbo ; Merialdo, Bernard
Author_Institution :
EURECOM, Sophia Antipolis, France
fYear :
2011
fDate :
13-15 June 2011
Firstpage :
163
Lastpage :
168
Abstract :
In this paper we propose a novel algorithm for video summarization, OB-MMR (Optimized Balanced Audio Video Maximal Marginal Relevance). This algorithm is suitable to summarize both single and multiple videos. OB-MMR is achieved by optimizing the parameters in Balanced AV-MMR (Balanced Audio Video Maximal Marginal Relevance), namely the balance factor between audio information and visual information in the video, but also the importance of face and audio transitions among audio segments with different genres. Therefore, OB-MMR achieves a better result than previous algorithms, Video-MMR and Balanced AV-MMR. Furthermore, it is possible to select the optimized parameters for each genre of videos, which leads to promising automatic algorithms for video summarization in the future large-scale experiments.
Keywords :
video retrieval; OB-MMR; audio information; multivideo summarization; optimized balanced audio video maximal marginal relevance; visual information; Entropy; Face; Fitting; Humans; Multimedia communication; Speech; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Content-Based Multimedia Indexing (CBMI), 2011 9th International Workshop on
Conference_Location :
Madrid
ISSN :
1949-3983
Print_ISBN :
978-1-61284-432-9
Electronic_ISBN :
1949-3983
Type :
conf
DOI :
10.1109/CBMI.2011.5972539
Filename :
5972539
Link To Document :
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