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1、Saliency-basedDiscriminantTrackingVijayMahadevanNunoVasconcelosDepartmentofElectricalandComputerEngineeringUniversityofCalifornia,SanDiegovmahadev@ucsd.edu,nuno@ece.ucsd.eduAbstractingboxatvideoframet,aclassifieristrainedtodistinguishtargetfeaturesfromthoseofthebackground.Thisclassi-
2、Weproposeabiologicallyinspiredframeworkforvisualfieristhenusedtodeterminethelocationofthetargetintrackingbasedondiscriminantcentersurroundsaliency.framet+1.Theboundingboxismovedtothislocation,Ateachframe,discriminationofthetargetfromtheback-theclassifierupdated,andtheprocessiterated.g
3、roundisposedasabinaryclassificationproblem.FromaInthebiologicalworld,objecttrackingiscloselyrelatedpooloffeaturedescriptorsforthetargetandbackground,atoattentionaltasks,suchastheguidanceofeyemovements.subsetthatismostinformativeforclassificationbetweentheDuetotheevolutionaryadvantages
4、ofsolvingthesetaskstwoisselectedusingtheprincipleofmaximummarginaldi-accurately,itisnotsurprisingthatbiologicalvisionsystemsversity.Usingthesefeatures,thelocationofthetargetinthehavedevelopedextremelyefficienttrackingmechanisms,nextframeisidentifiedusingtop-downsaliency,complet-interm
5、sofbothaccuracyandspeed.Theeffectivenessofingoneiterationofthetrackingalgorithm.Wealsoshowthesemechanisms,evenunderthemostadverseconditionsthatasimpleextensionoftheframeworktoincludemotion(e.g.highlyclutteredscenes,low-light,etc),isaconse-featuresinabottom-upsaliencymodecanrobustlyi
6、den-quenceoftheavailabilityofrobustsaliencymechanisms,tifysalientmovingobjectsandautomaticallyinitializethethatcausepre-attentivepop-outofsalientlocationsinthetracker.Theconnectionsoftheproposedmethodtoexistingvisualfield[23].Thesesalientlocationsbecomethefocusworksondiscriminanttrac
7、kingarediscussed.Experimen-ofattention(FoA)forthepost-attentivestagesofvisualpro-talresultscomparingtheproposedmethodtothestateofcessing,wheretop-downfeedbackfromhigherlevelcorti-theartintrackingarepresented,showingimprovedperfor-callayersisusedtosolveproblemssuchastrackingorvi-manc
8、e.sualsearch[31]wit