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