Article

Entropy metrics used for video summarization

Authors:

Z. ¯Cerneková,

I. PitasAuthors Info & Claims

SCCG '02: Proceedings of the 18th Spring Conference on Computer Graphics

Pages 73 - 82

https://doi.org/10.1145/584458.584471

Published: 24 April 2002 Publication History

Abstract

New methods for detecting shot boundaries in video sequences and for extracting key frames using metrics based on information theory are proposed. The method for shot cut detection relies on the mutual information and the joint entropy between the frames. It can detect cuts, fade-ins and fade-outs. The detection technique was tested on TV video sequences having different types of shots and containing significant object and camera motion inside the shots. It is demonstrated that the method detects both fades and abrupt cuts with high accuracy. The method for key frame extraction is using the mutual information. We show that it captures satisfactorily the visual content of the shot.

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Cited By

Alksne LOzols A(2022)Maximum Shannon Information Delivered in a LectureLatvian Journal of Physics and Technical Sciences10.2478/lpts-2022-000859:2(12-22)Online publication date: 22-Apr-2022
https://doi.org/10.2478/lpts-2022-0008
Raikwar SBhatnagar CJalal A(2019)A Novel Framework for Efficient Extraction of Meaningful Key Frames From Surveillance VideoCensorship, Surveillance, and Privacy10.4018/978-1-5225-7113-1.ch019(342-359)Online publication date: 2019
https://doi.org/10.4018/978-1-5225-7113-1.ch019
Raikwar SBhatnagar CJalal A(2015)A Novel Framework for Efficient Extraction of Meaningful Key Frames from Surveillance VideoInternational Journal of System Dynamics Applications10.4018/ijsda.20150401044:2(56-73)Online publication date: 1-Apr-2015
https://doi.org/10.4018/ijsda.2015040104
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Index Terms

Entropy metrics used for video summarization
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision

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cover image ACM Conferences

SCCG '02: Proceedings of the 18th Spring Conference on Computer Graphics

April 2002

198 pages

ISBN:1581136080

DOI:10.1145/584458

Conference Chair:
Alan Chalmers
University of Bristol, UK

Copyright © 2002 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 24 April 2002

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PCK50

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SIGGRAPH

PCK50: Principles of Computing Knowledge: Paris C. Kanellakis Memorial Workshop

April 24 - 27, 2002

Budmerice, Slovakia

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Overall Acceptance Rate 42 of 81 submissions, 52%

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Cited By

Alksne LOzols A(2022)Maximum Shannon Information Delivered in a LectureLatvian Journal of Physics and Technical Sciences10.2478/lpts-2022-000859:2(12-22)Online publication date: 22-Apr-2022
https://doi.org/10.2478/lpts-2022-0008
Raikwar SBhatnagar CJalal A(2019)A Novel Framework for Efficient Extraction of Meaningful Key Frames From Surveillance VideoCensorship, Surveillance, and Privacy10.4018/978-1-5225-7113-1.ch019(342-359)Online publication date: 2019
https://doi.org/10.4018/978-1-5225-7113-1.ch019
Raikwar SBhatnagar CJalal A(2015)A Novel Framework for Efficient Extraction of Meaningful Key Frames from Surveillance VideoInternational Journal of System Dynamics Applications10.4018/ijsda.20150401044:2(56-73)Online publication date: 1-Apr-2015
https://doi.org/10.4018/ijsda.2015040104
Zdziarski ZBourges CMitchell JHoudyer PJohnson DDahyot R(2014)On summarising the ‘here and now’ of social videos for smart mobile browsing2014 International Workshop on Computational Intelligence for Multimedia Understanding (IWCIM)10.1109/IWCIM.2014.7008797(1-5)Online publication date: Nov-2014
https://doi.org/10.1109/IWCIM.2014.7008797
Kuanar SPanda RChowdhury A(2013)Video key frame extraction through dynamic Delaunay clustering with a structural constraintJournal of Visual Communication and Image Representation10.1016/j.jvcir.2013.08.00324:7(1212-1227)Online publication date: 1-Oct-2013
https://dl.acm.org/doi/10.1016/j.jvcir.2013.08.003
Takenaka KBando TNagasaka STaniguchi TBabaguchi NAizawa KSmith JSatoh SPlagemann THua XYan R(2012)Drive video summarization based on double articulation structure of driving behaviorProceedings of the 20th ACM international conference on Multimedia10.1145/2393347.2396410(1169-1172)Online publication date: 29-Oct-2012
https://dl.acm.org/doi/10.1145/2393347.2396410
Jiang JZhang X(2010)A new player-enabled rapid video navigation method using temporal quantization and repeated weighted boosting search2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops10.1109/CVPRW.2010.5543733(64-71)Online publication date: Jun-2010
https://doi.org/10.1109/CVPRW.2010.5543733
Xiao ZPoursoltanmohammadi ASorell MSorell M(2008)Video motion detection beyond reasonable doubtProceedings of the 1st international conference on Forensic applications and techniques in telecommunications, information, and multimedia and workshop10.5555/1363217.1363225(1-6)Online publication date: 21-Jan-2008
https://dl.acm.org/doi/10.5555/1363217.1363225
Das SSural SMajumdar A(2008)Detection of hard cuts and gradual transitions from video using fuzzy logicInternational Journal of Artificial Intelligence and Soft Computing10.1504/IJAISC.2008.0212651:1(77-98)Online publication date: 1-Nov-2008
https://dl.acm.org/doi/10.1504/IJAISC.2008.021265
Lee DKim HKim EYan SChen JLee J(2008)LeeDeoProceedings of the 2008 Tenth IEEE International Symposium on Multimedia10.1109/ISM.2008.105(497-502)Online publication date: 15-Dec-2008
https://dl.acm.org/doi/10.1109/ISM.2008.105
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