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Video redundancy detection in rushes collection

Authors:

Reede Ren,

P. Punitha,

Joemon JoseAuthors Info & Claims

TVS '08: Proceedings of the 2nd ACM TRECVid Video Summarization Workshop

Pages 65 - 69

https://doi.org/10.1145/1463563.1463574

Published: 31 October 2008 Publication History

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Abstract

The rushes is a collection of raw material videos. There are various redundancies, such as rainbow screen, clipboard shot, white/black view, and unnecessary re-take. This paper develops a set of solutions to remove these video redundancies as well as an effective system for video summarisation. We regard manual editing effects, e.g. clipboard shots, as differentiators in the visual language. A rushes video is therefore divided into a group of subsequences, each of which stands for a re-take instance. A graph matching algorithm is proposed to estimate the similarity between re-takes and suggests the best instance for content presentation. The experiments on the Rushes 2008 collection show that a video can be shortened to 4%-16% of the original size by redundancy detection. This significantly reduces the complexity in content selection and leads to an effective and efficient video summarisation system.

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Park HCho S(2011)A personalized summarization of video life-logs from an indoor multi-camera system using a fuzzy rule-based system with domain knowledgeInformation Systems10.1016/j.is.2011.04.00536:8(1124-1134)Online publication date: Dec-2011
https://doi.org/10.1016/j.is.2011.04.005
Over PSmeaton AAwad GOver PSmeaton A(2008)The trecvid 2008 BBC rushes summarization evaluationProceedings of the 2nd ACM TRECVid Video Summarization Workshop10.1145/1463563.1463564(1-20)Online publication date: 31-Oct-2008
https://dl.acm.org/doi/10.1145/1463563.1463564

Index Terms

Video redundancy detection in rushes collection
1. Information systems
  1. Information storage systems
    1. Record storage systems
  2. Information systems applications

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In this paper, we describe our approach to the TRECVID 2008 BBC Rushes Summarization task. First, we remove junk frames and dynamically accelerate videos according to their motion activity to maximize the content per time unit. Then, we search identical ...

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TVS '08: Proceedings of the 2nd ACM TRECVid Video Summarization Workshop

October 2008

156 pages

ISBN:9781605583099

DOI:10.1145/1463563

General Chairs:
Paul Over
NIST, USA
,
Alan F. Smeaton
Dublin City University, Ireland

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Published: 31 October 2008

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MM08: ACM Multimedia Conference 2008

October 31, 2008

British Columbia, Vancouver, Canada

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Park HCho S(2011)A personalized summarization of video life-logs from an indoor multi-camera system using a fuzzy rule-based system with domain knowledgeInformation Systems10.1016/j.is.2011.04.00536:8(1124-1134)Online publication date: Dec-2011
https://doi.org/10.1016/j.is.2011.04.005
Over PSmeaton AAwad GOver PSmeaton A(2008)The trecvid 2008 BBC rushes summarization evaluationProceedings of the 2nd ACM TRECVid Video Summarization Workshop10.1145/1463563.1463564(1-20)Online publication date: 31-Oct-2008
https://dl.acm.org/doi/10.1145/1463563.1463564

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Attention-based video summarisation in rushes collection

Rushes video summarization using audio-visual information and sequence alignment

Sequence alignment for redundancy removal in video rushes summarization

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