Abstract The MediaMill TRECVID 2005 Semantic Video Search En(16)

UvA-MediaMill team participated in four tasks. For the detection of camera work (runid: A CAM) we investigate the benefit of using a tessellation of detectors in combination with supervised learning over a standard approach using global image information.

beexpectedfromimprovedvisualanalysisyieldingalargelexiconofsemanticconcepts.

Acknowledgements

NISTfortheevaluatione ort.KevinWalkerforsolvingharddiskproblems.DCUteamforcreationofkeyframes.AlexHauptmannformissingmachinetranslations.

References

[1]A.Amiretal.IBMresearchTRECVID-2003videoretrieval

system.InProc.oftheTRECVIDWorkshop,Gaithersburg,USA,2003.

[2]zyusersandautomaticvideoretrievaltools

in(the)lowlands.InE.VoorheesandD.Harman,editors,Proc.ofthe10thTextREtrievalConference,volume500-250,Gaithersburg,USA,2001.

[3]BlinkxVideoSearch,2005./.[4]C.-C.ChangandC.-J.Lin.LIBSVM:alibraryfor

supportvectormachines,2001.Softwareavailableathttp://www.csie.ntu.edu.tw/~cjlin/libsvm/.

[5]S.Deerwester,S.Dumais,G.Furnas,ndauer,and

R.Harshman.Indexingbylatentsemanticanalysis.J.AmericanSocietyInform.Science,41(6):391–407,1990.[6]J.Geusebroek.Visualobjectrecognition,2005.Patent

PCT/NL2005/000485 ledJuly6.

[7]J.Geusebroek,R.Boomgaard,A.Smeulders,and

H.Geerts.Colorinvariance.IEEETrans.PAMI,23(12):1338–1350,2001.

[8]J.GeusebroekandA.W.M.Smeulders.Asix-stimulusthe-oryforstochastictexture.InternationalJournalofCom-puterVision,62(1/2):7–16,2005.

[9]GoogleVideoSearch,2005./.[10]B.Huurnink.AutoSeek:Towardsafullyautomatedvideo

searchsystem.Master’sthesis,UniversiteitvanAmster-dam,2005.

[11]A.Jain,R.Duin,andJ.Mao.Statisticalpatternrecogni-tion:Areview.IEEETrans.PAMI,22(1):4–37,2000.

[12]P.JolyandH.-K.Kim.E cientautomaticanalysisofcam-eraworkandmicrosegmentationofvideousingspatiotem-poralimages.SignalProcessing:ImageCommunication,8(4):295–307,1996.

[13]G.Miller.WordNet:-municationsoftheACM,38(11):39–41,1995.

[14]M.Naphade.Onsupervisionandstatisticallearningfor

semanticmultimediaanalysis.J.VisualCommun.ImageRepresentation,15(3):348–369,2004.

[15]G.NguyenandM.Worring.Similaritybasedvisualization

ofimagecollections.InInt’lWorksh.Audio-VisualContentandInformationVisualizationinDigitalLibraries,2005.[16]NIST.TRECVIDVideoRetrievalEvaluation,2001–2005.

http://www-nlpir.nist.gov/projects/trecvid/.

[17]T.Pedersen,S.Patwardhan,andJ.Michelizzi.Word-Net:Similarity-measuringtherelatednessofconcepts.InNat’lConf.Arti cialIntelligence,SanJose,USA,2004.[18]C.Petersohn.FraunhoferHHIatTRECVID2004:Shot

boundarydetectionsystem.InProc.oftheTRECVIDWorkshop,Gaithersburg,USA,2004.

[19]J.Platt.ProbabilitiesforSVmachines.InAdvancesin

LargeMarginClassi ers,pages61–74.MITPress,2000.

[20]M.Porter.Analgorithmforsu xstripping.Program,

14(3):130–137,1980.

[21]inginformationcontenttoevaluatesemantic

similarityinataxonomy.InInternationalJointConferenceonArti cialIntelligence,SanMateo,USA,1995.

[22]O.Rooij.Browsingnewsvideousingsemanticthreads.

Master’sthesis,UniversiteitvanAmsterdam,2006.

[23]G.Salton.TheSMARTretrievalsystem:experimentsin

automaticdocumentprocessing.Prentice-Hall,EnglewoodCli s,USA,1971.

[24]G.SaltonandC.Buckley.Term-weightingapproachesin

rmationProcessingandMan-agement,24(5):513–523,1988.

[25]T.Sato,T.Kanade,E.Hughes,M.Smith,andS.Satoh.

VideoOCR:Indexingdigitalnewslibrariesbyrecognitionofsuperimposedcaption.MultimediaSystems,7(5):385–395,1999.

[26]H.Schmid.Probabilisticpart-of-speechtaggingusingdeci-siontrees.InInternationalConferenceonNewMethodsinLanguageProcessing,Manchester,UK,1994.

[27]H.SchneidermanandT.Kanade.Objectdetectionusing

thestatisticsofparts.InternationalJournalofComputerVision,56(3):151–177,2004.

[28]A.Smeulders,M.Worring,S.Santini,A.Gupta,and

R.Jain.Contentbasedimageretrievalattheendoftheearlyyears.IEEETrans.PAMI,22(12):1349–1380,2000.[29]C.SnoekandM.Worring.Multimediaevent-basedvideo

indexingusingtimeintervals.IEEETrans.Multimedia,7(4):638–647,2005.

[30]C.Snoek,M.Worring,J.Geusebroek,D.Koelma,F.Sein-stra,andA.Smeulders.Thesemanticpath nder:Usinganauthoringmetaphorforgenericmultimediaindexing.IEEETrans.PAMI,2006.Inpress.

[31]C.Snoek,M.Worring,andA.Hauptmann.Learningrich

semanticsfromnewsvideoarchivesbystyleanalysis.ACMTrans.MultimediaComputing,CommunicationsandAppli-cations,2(2),May2006.inpress.

[32]C.Snoek,M.Worring,andA.Smeulders.Earlyversus

latefusioninsemanticvideoanalysis.InACMMultimedia,Singapore,2005.

[33]S.TongandE.Chang.Supportvectormachineactivelearn-ingforimageretrieval.InACMMultimedia,pages107–118,Ottawa,Canada,2001.

[34]Y.Tonomura,A.Akutsu,Y.Taniguchi,andG.Suzuki.

Structuredvideocomputing.IEEEMultimedia,1(3):34–43,1994.

[35]V.Vapnik.TheNatureofStatisticalLearningTheory.

Springer-Verlag,NewYork,USA,2thedition,2000.

[36]T.Volkmer,J.Smith,A.Natsev,M.Campbell,and

M.Naphade.Aweb-basedsystemforcollaborativeanno-tationoflargeimageandvideocollections.InACMMulti-media,Singapore,2005.

[37]T.Westerveld,R.Cornacchia,J.vanGemert,D.Hiemstra,

andA.deVries.Anintegratedapproachtotextandimageretrieval–thelowlandsteamatTRECVID2005.InProc.oftheTRECVIDWorkshop,Gaithersburg,USA,2005.[38]X.ZhouandT.Huang.Relevancefeedbackinimagere-trieval:acomprehensiveoverview.MultimediaSystems,8(6):536–544,2003.