Range Segmentation Using Visibility Constraints

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RangeSegmentationUsingVisibilityConstraintsLeonidTaycher&TrevorDarrellArtificialIntelligenceLaboratoryMassachusettsInstituteofTechnologyCambridge,Massachusetts02139

http://www.ai.mit.edu@ MIT

TheProblem:Wearelookingtoproduceaforegroundsegmentationmechanismthatwouldworkunderwidelyvaryingilluminationconditions.

Motivation:Oneofthemostimportanttasksofcomputervisioninintelligentenvironmentsisdetectingandtrackingvariousobjects(includinghumans).Thestate-of-the-artsystemsuseforeground/backgroundclassificationfollowedbyforegroundpixelclusteringandclusteranalysis.Thesesystemscommonlymaintainabackgroundmodelandlabelallpixelsthatdiffersignificantlyfromthismodelasforeground.

Sinceasegmentationalgorithmforpersontrackingshouldworkingeneralenvironments,itshouldberobusttofrequentandsuddenilluminationchanges,e.g.,duetooutdoorlightingvariationsorindoorvideoprojection.Stereorange-basedmethodshavebecomepopularandcansatisfythisrequirementwhendenserangedataareavailable.However,manyenvironmentshavebackgroundsthataresparse,suchasindoorwalls.Intheseenviron-mentssimplebackgroundrangemodelsareproblematic,sincethereisaninherentambiguityinclassifyingavalidrangevalueinthelocationwherethemodelcontainsaninvalidrangevalue.Evenwhenmultiplestereoviewsareavailable[3],sparsebackgroundscanmakeitdifficulttodetectpeople.

PreviousWork:Severalsegmentationmethodshavebeenproposedwhichusebackgroundmodelsbasedoncolor/intensity[6],stereorange[3]orboth[2].Generally,non-adaptivecolor-basedmodelssufferfromvaryingillumination.Adaptivecolormodelscanbemorestabletolightingchanges,butcanerroneouslyincorporateob-jectsthatstopmovingintothebackgroundmodel.Range-basedbackgroundmodelscanbeilluminationinvariant,butareusuallysparse.Toavoidambiguityatundefinedbackgroundvalues(andtheresultingilluminationde-pendence[1]),theyareeitherusedinconjunctionwithcolormodels,orarebuiltusingobservationsfromwidelyvaryingilluminationandimagingconditions[1].

Toovercometheambiguitiesinasingleview,informationaboutfreespaceconstraintsovermultipleviewsmaybeused.Variousvoxelcoloringandspacecarvingmethods[4]splitthespaceintovoxelsandusecolorconsistencyacrossmultiplecamerastolocateopaquevoxelsandtodetectfreespace.Thesemethodsarequitegeneral,andworkwithanarbitrarysetofmonocularviews.Theyalsorequiretheconstructionofavolumetricrepresentationofthesceneforreconstructionorsegmentation.Weareinterestedinalgorithmsthatperformsegmentationsolelyintheimagedomain,withoutcomputingavolumetricreconstruction.

Approach:Ourapproachtoforegroundsegmentationistocombinefreespaceconstraintsfoundfrommultiplestereorangeviews.Wedecideifagivenpixelis“foreground”bycheckingwhetherthereisanyfreespacebehindit,asseenfromotherrangeviews.Wescanthesetofepipolarlinesintheotherviewscorrespondingtothegivenpixel,andtestwhethertherearerangepointsontheepipolarlineswhichindicateemptyspacebehindthegivenpoint(Figure1.Thisisasimilarcomputationtoalgorithmsproposedfortherenderingoftheimage-basedvisualhulls[5].Thekeydifferenceisthatourmethodtakesasinputunsegmentednoisyrangedataandevaluates3-Dvisibilityperray,whilethevisualhullmethodpresumessegmentedcolorimagesasinputandsimplyidentifiesnon-emptypixelsalongtheepipolarlinesinotherviews.Webelieveoursisthefirstmethodforrangeimagesegmentationusingimage-based(non-voxel)freespacecomputation.

FutureWork:WeareplanningtoincorporatethissegmentationmechanismintoIntelligentRoompersontrackingandVisualHull[5]computation.

ResearchSupport:ThisprojectisfundedwiththegeneroussupportoftheDarpaHumanIDprogram.

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Figure1:Visibility-basedsegmentation.PointBvisibleinI2(projectingtoC2disparitypointb)liesbehindpointPrelativetoC2,andthusprovidesevidenceforexistenceoffreespacebehindP(projectingtob)bydemonstrating

thatPistransparent.Linelcontainstheoversilhouetteforthepartofanobjectlyingalongray[C1,P)

References:[1]T.Darrell,D.Demirdjian,N.Checka,andP.Felzenszwalb.Plan-viewtrajectoryestimationwithdensestereobackgroundmodels.InProc.InternationalConferenceonComputerVision(ICCV’01),2001.

[2]M.Harville,G.Gordon,andJ.Woodfill.Foregroundsegmentationusingadaptivemixturemodelsincoloranddepth.InWorkshoponDetectionandRecognitionofEventsinVideo.,2001.

[3]J.Krumm,S.Harris,B.Meyers,B.Brumitt,M.Hale,andS.Shafer.Multi-cameramulti-persontrackingforeasyliving.InIEEEWorkshoponVisualSurveillance,July2000.

[4]K.N.KutulakosandS.M.Seitz.Atheoryofshapebyspacecarving.Int.JournalofComputerVision,38(3):199–218,July2000.

[5]WojciechMatusik,ChrisBuehler,RameshRaskar,StevenJ.Gortler,andLeonardMcMillan.Image-basedvisualhulls.InKurtAkeley,editor,Siggraph2000,ComputerGraphicsProceedings,AnnualConferenceSeries,pages369–374.ACMPress/ACMSIGGRAPH/AddisonWesleyLongman,2000.