Impairment of Shooting Performance by Background Complexity and Motion

Similar documents
Methylation-associated PHOX2B gene silencing is a rare event in human neuroblastoma.

Easter bracelets for years

A new simple recursive algorithm for finding prime numbers using Rosser s theorem

Smart Bolometer: Toward Monolithic Bolometer with Smart Functions

L institution sportive : rêve et illusion

Passerelle entre les arts : la sculpture sonore

Evolution of the cooperation and consequences of a decrease in plant diversity on the root symbiont diversity

Thomas Lugand. To cite this version: HAL Id: tel

Completeness of the Tree System for Propositional Classical Logic

Dispersion relation results for VCS at JLab

Can we reduce health inequalities? An analysis of the English strategy ( )

On size, radius and minimum degree

Soundness of the System of Semantic Trees for Classical Logic based on Fitting and Smullyan

Case report on the article Water nanoelectrolysis: A simple model, Journal of Applied Physics (2017) 122,

Analysis of Boyer and Moore s MJRTY algorithm

On Symmetric Norm Inequalities And Hermitian Block-Matrices

Vibro-acoustic simulation of a car window

From Unstructured 3D Point Clouds to Structured Knowledge - A Semantics Approach

Entropies and fractal dimensions

b-chromatic number of cacti

On Symmetric Norm Inequalities And Hermitian Block-Matrices

A new approach of the concept of prime number

On the longest path in a recursively partitionable graph

Full-order observers for linear systems with unknown inputs

A Simple Proof of P versus NP

Basic concepts and models in continuum damage mechanics

The Learner s Dictionary and the Sciences:

Territorial Intelligence and Innovation for the Socio-Ecological Transition

The FLRW cosmological model revisited: relation of the local time with th e local curvature and consequences on the Heisenberg uncertainty principle

A Context free language associated with interval maps

3D-CE5.h: Merge candidate list for disparity compensated prediction

Reduced Models (and control) of in-situ decontamination of large water resources

Exogenous input estimation in Electronic Power Steering (EPS) systems

Numerical Modeling of Eddy Current Nondestructive Evaluation of Ferromagnetic Tubes via an Integral. Equation Approach

STATISTICAL ENERGY ANALYSIS: CORRELATION BETWEEN DIFFUSE FIELD AND ENERGY EQUIPARTITION

Impulse response measurement of ultrasonic transducers

A Study of the Regular Pentagon with a Classic Geometric Approach

Parallel Repetition of entangled games on the uniform distribution

FORMAL TREATMENT OF RADIATION FIELD FLUCTUATIONS IN VACUUM

Hook lengths and shifted parts of partitions

Towards an active anechoic room

Theoretical calculation of the power of wind turbine or tidal turbine

A non-commutative algorithm for multiplying (7 7) matrices using 250 multiplications

Sound intensity as a function of sound insulation partition

Determination of absorption characteristic of materials on basis of sound intensity measurement

Stochastic invariances and Lamperti transformations for Stochastic Processes

There are infinitely many twin primes 30n+11 and 30n+13, 30n+17 and 30n+19, 30n+29 and 30n+31

BERGE VAISMAN AND NASH EQUILIBRIA: TRANSFORMATION OF GAMES

The Windy Postman Problem on Series-Parallel Graphs

SOLAR RADIATION ESTIMATION AND PREDICTION USING MEASURED AND PREDICTED AEROSOL OPTICAL DEPTH

A simple kinetic equation of swarm formation: blow up and global existence

Particle-in-cell simulations of high energy electron production by intense laser pulses in underdense plasmas

Quantum efficiency and metastable lifetime measurements in ruby ( Cr 3+ : Al2O3) via lock-in rate-window photothermal radiometry

A remark on a theorem of A. E. Ingham.

Spatial representativeness of an air quality monitoring station. Application to NO2 in urban areas

Two-step centered spatio-temporal auto-logistic regression model

New estimates for the div-curl-grad operators and elliptic problems with L1-data in the half-space

Solubility prediction of weak electrolyte mixtures

Exact Comparison of Quadratic Irrationals

Multiple sensor fault detection in heat exchanger system

The Riemann Hypothesis Proof And The Quadrivium Theory

Impedance Transmission Conditions for the Electric Potential across a Highly Conductive Casing

A Slice Based 3-D Schur-Cohn Stability Criterion

On infinite permutations

Water Vapour Effects in Mass Measurement

IMPROVEMENTS OF THE VARIABLE THERMAL RESISTANCE

Comment on: Sadi Carnot on Carnot s theorem.

Gaia astrometric accuracy in the past

Comparison of Harmonic, Geometric and Arithmetic means for change detection in SAR time series

Influence of network metrics in urban simulation: introducing accessibility in graph-cellular automata.

Factorisation of RSA-704 with CADO-NFS

Finite Volume for Fusion Simulations

On Poincare-Wirtinger inequalities in spaces of functions of bounded variation

New Basis Points of Geodetic Stations for Landslide Monitoring

On the Griesmer bound for nonlinear codes

The status of VIRGO. To cite this version: HAL Id: in2p

Control of an offshore wind turbine modeled as discrete system

Characterization of Equilibrium Paths in a Two-Sector Economy with CES Production Functions and Sector-Specific Externality

Solving a quartic equation and certain equations with degree n

On Politics and Argumentation

Lorentz force velocimetry using small-size permanent magnet systems and a multi-degree-of-freedom force/torque sensor

Christian Défarge, Pascale Gautret, Joachim Reitner, Jean Trichet. HAL Id: insu

Unfolding the Skorohod reflection of a semimartingale

Stickelberger s congruences for absolute norms of relative discriminants

Solving the neutron slowing down equation

Best linear unbiased prediction when error vector is correlated with other random vectors in the model

Sparse multivariate factorization by mean of a few bivariate factorizations

ATOMIC STRUCTURE OF INTERFACES IN GaAs/Ga1-xAlxAs SUPERLATTICES

Prompt Photon Production in p-a Collisions at LHC and the Extraction of Gluon Shadowing

RHEOLOGICAL INTERPRETATION OF RAYLEIGH DAMPING

AC Transport Losses Calculation in a Bi-2223 Current Lead Using Thermal Coupling With an Analytical Formula

On one class of permutation polynomials over finite fields of characteristic two *

The spreading of fundamental methods and research design in territorial information analysis within the social sciences and humanities

Solution to Sylvester equation associated to linear descriptor systems

Question order experimental constraints on quantum-like models of judgement

LAWS OF CRYSTAL-FIELD DISORDERNESS OF Ln3+ IONS IN INSULATING LASER CRYSTALS

Numerical modification of atmospheric models to include the feedback of oceanic currents on air-sea fluxes in ocean-atmosphere coupled models

Posterior Covariance vs. Analysis Error Covariance in Data Assimilation

Higgs searches at L3

Learning an Adaptive Dictionary Structure for Efficient Image Sparse Coding

Transcription:

Impairment of Shooting Performance by Background Complexity and Motion Loïc Caroux, Ludovic Le Bigot, Nicolas Vibert To cite this version: Loïc Caroux, Ludovic Le Bigot, Nicolas Vibert. Impairment of Shooting Performance by Background Complexity and Motion. Experimental Psychology, Hogrefe, 2015, 62 2), pp.98-109. <10.1027/1618-3169/a000277>. <hal-01097375> HAL Id: hal-01097375 https://hal.inria.fr/hal-01097375 Submitted on 19 Dec 2014 HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

PRE$PRINT$ Caroux,L.,LeBigot,L.,&Vibert,N.inpress).Impairmentofshootingperformanceby backgroundcomplexityandmotion.experimental,psychology.doi:10.1027/1618j3169/a000277 This,article,may,not,exactly,replicate,the,final,version,published,in,Experimental,Psychology,, 2014,by,Hogrefe,Publishing.,It,is,not,the,version,of,record,and,is,therefore,not,suitable,for,citation., Title: Impairmentofshootingperformancebybackgroundcomplexityandmotion Authors: LoïcCAROUX,LudovicLEBIGOT,NicolasVIBERT Affiliation: CentredeRecherchessurlaCognitionetl ApprentissageCeRCA) UMR7295 UniversityofPoitiers/UniversityofTours/CNRS France LoïcCarouxiscurrentlyaffiliatedtoINRIABordeauxSudWOuest,Talence,France) Correspondingauthor: LoïcCaroux INRIABordeauxSudWOuest EquipePhoenix 200avenuedelaVieilleTour 33405TalenceCedex France Email:loic.caroux@inria.fr 1

Abstract Inmanyvisualdisplayssuchasvirtualenvironments,humantasksinvolveobjectssuperimposedon bothcomplexandmovingbackgrounds.however,moststudiesinvestigatedtheinfluenceof backgroundcomplexityorbackgroundmotioninisolation.twoexperimentsweredesignedto investigatethejointinfluencesofbackgroundcomplexityandlateralmotiononasimpleshooting tasktypicalofvideogames.participantshadtoperformthetaskonthemovingandstaticversionsof backgroundsofthreelevelsofcomplexity,whiletheireyemovementswererecorded.the backgroundsdisplayedeitheranabstractexperiment1)oranaturalisticexperiment2)virtual environment.theresultsshowedthatperformancewasimpairedbybackgroundmotioninboth experiments.theeffectsofmotionandcomplexitywereadditivefortheabstractbackgroundand multiplicativeforthenaturalisticbackground.eyemovementrecordingsshowedthatperformance impairmentsreflectedatleastinparttheimpactofthebackgroundvisualfeaturesongazecontrol. Keywords Eyemovements;LowWlevelvisualfeatures;Virtualenvironments;Visualperception 2

1. Introduction$ Invirtualenvironments,mosttasksinvolvetheuseofobjectsthataresuperimposedona background.ingeneral,thesebackgroundsarecomplexanddynamicasinnaturalscenes.theyare composedofvariousvisualinformatione.g.,buildinginsides,landscapes)andcanmoveindifferent wayse.g.,linearorcircularmotion)inconnectionwiththetaskinwhichpeopleareengagede.g., Riecke,SchulteWPelkum,Avraamides,VonDerHeyde,&Bülthoff,2006;Trutoiu,Mohler,SchulteW Pelkum,&Bülthoff,2009). Asdetailedbelow,manystudieshaveshownthatbackgroundcomplexitye.g.,Chen&Hegdé,2012; Jie&Clark,2008;Wolfe,Oliva,Horowitz,Butcher,&Bompas,2002)ormotione.g.,Caroux,LeBigot, &Vibert,2013;Harrison,Thompson,&Sanderson,2010;Honda,2001;Kaminiarz,Krekelberg,& Bremmer,2007;Tozzi,Morrone,&Burr,2007)couldimpairpeople sperformanceinvarioustasks andsituations.ingeneral,theimpairmentcanbeexplainedbythepeople sgazebehavior,which reflectsattentionalprocessese.g.,henderson,chanceaux,&smith,2009;ilg,1997).however,few studiesinvestigatedthejointeffectsofbackgroundmotionandcomplexity.theobjectiveofthe presentexperimentswastofillthisgapbyinvestigatingthejointinfluencesofbackground complexityandbackgroundmotiononperformanceandgazebehaviorinavirtualenvironment. 1.1. Influence$of$background$complexity$on$performance$and$gaze$ behavior$ ThecomplexityofavisualsceneisusuallycharacterizedbylowWlevelvisualfeatures.Toqualifythe complexityofavisualscene,theconceptof clutter canbeusede.g.,asher,tolhurst,troscianko,& Gilchrist,2013;Beck,Lohrenz,&Trafton,2010;Neider&Zelinsky,2011;Wolfeetal.,2002).The clutterrepresentsthedensityofvisualinformationinascene.whentheclutterofavisualsceneis high,thesceneincludesagreatdensityofvariouscolororluminancecontrasts.whentheclutteris 3

low,onlyfewcontrastsarevisibleinthescene.thecomplexityofavisualscenehasanimpacton people sperformanceandassociatedgazebehaviorhendersonetal.,2009)invarioustasks,suchas visualsearche.g.,wolfeetal.,2002)orvideogameshootingtasksjie&clark,2008). Wolfeetal.2002)studiedvisualsearchincomplexvisualenvironmentsandproposedamodel basedonthe guidedsearch modelwolfe,1994).searchingforaniteminacomplexvisualscene canbeseparatedintwostages:theprewattentivestageandtheselectivestage.inthefirststage, parallelprocessingofvisualinformationisusedtoguidethedeploymentofattention,andcandidate targetsaresegmentedfromthebackground.inthesecondstage,attentionisorientedtowardsthe prewselecteditems,whichareprocessedfurthertoidentifythetarget.wolfeetal.2002)showed thatthemorecomplexthescenewas,themoreimperfecttheprewattentivesegmentationwas.in addition,thedurationofprocessingofprewselecteditemsdependedonthequalityoftheseparation ofitemsfromthebackground.hence,themorecomplexthevisualenvironmentwas,thelowerthe observer sperformancewasandtheslowertheobserversweretodetectthetarget.similarly,jie andclark2008)studiedtheeffectofbackgroundcomplexityontheperceptionofsuperimposed itemsinashootingtask.participantshadtodetecttargetsthatappearedrandomlyonastationary complexpicture,andtoshootthemasrapidlyaspossible.theauthorsshowedthatperformance timetoshoottargets)waslowerwhenthelocalclutteraroundthetargetwashigher. Thetimetoprocessadisplaycanalsobeassessedbyanalyzingobservers eyemovementsfora review,seerayner,2009).forexample,thedurationofsearchers eyefixationsisoftenusedto quantifytheamountofattentionalresourcesrequiredtoprocessvisualitemsintheenvironment. Hendersonetal.2009)showedthatinarealworldscene,themorecomplexthescenewas,the higherthemeandurationofeyefixationswas.thiswascoherentwithwolfeetal. s2002)findings aboutthetimeneededtodetectthetargetduringavisualsearchtaskperformedonacomplex background.thisreflectedthedifficultyfortheobservertoextractusefulinformationfromthelocal 4

visual noise.hence,themeandurationofeyefixationsisanindicatorofthesearchefficiency withinacomplexscene. 1.2. Influence$of$background$motion$on$gaze$behavior$and$ performance$ Oneofthebestknowneffectsofmovingbackgroundsinnaturalscenesorvirtualenvironmentsis theoptokineticnystagmusokn)triggeredbylargewscalemotionsofthevisualsurroundingse.g., Kim&Palmisano,2010;Rieckeetal.,2006).TheOKNisareflexive,conjugatemovementofboth eyesinwhichtwophasesalternate:theslowphasemovestheeyesinthedirectionofbackground motion,ideallyatthesamevelocity,whereasthefastphaseregularlybringsbacktheeyesinthe oppositedirectionilg,1997;waespe&schwarz,1987).theslowphaseoftheoknisa compensatoryeyemovementthatallowstheobservertoautomaticallykeepvisualinputstableon theretina.eventhoughtheslowandfastphasestendtocompensateeachother,theaveragegaze orientationisgenerallydivertedtowardswherethemovingscenecomesfrom,atleastwhenthe observerispassivelylookingatthesceneilg,1997).notethatanysingle,stationaryfixationpoint presentedontopofthemovingbackgroundcanbeusedbyobserverstovoluntarilycanceltheokn Ilg,1997). TheOKNhasbehavioralimplicationsforactivitiesperformedonmovingvisualbackgrounds.For example,theoknhasnegativeeffectsonobservers performanceinperceptivetasks.kaminiarzet al.2007)andtozzietal.2007)studiedtheimpactofoknonparticipants performanceinatarget localizationtask.participantshadtolocalizeabrieflyflashedtargetdisplayedonalaterallymoving, patternedbackground.theauthorsshowedthatvariouserrorsoflocalizationwereobservedduring OKNphases.Carouxetal.2013)studiedtheeffectofbackgroundmotionontheperceptionof superimposeditemsduringashootingtask.participantshadtodetecttargetsthatappeared randomlyonpatternedbackgrounds,andtoshootthemasrapidlyaspossible.theyshowedthat 5

performancetimetoshoottargets)waslowerwhenthebackgroundwaslaterallymovingthan whenitwasstationary.similarly,harrisonetal.2010)demonstratedthatbackgroundmotion decreasedperformanceinasimpletaskinvolvingtheintegrationofbriefauditoryandvisualsignals. ThevisualimagewasdisplayedonaheadWmounteddisplayandthebackgroundwastherealworld. Whentheparticipantswalkedorwhenthewallssurroundingtheparticipantsmoved,the performancewaslowerthanwhentheparticipantssatorwhenthewallswerestationary.insum, movingartificialorrealworldbackgroundsdooftendecreaseperformanceinsimpletaskssuchas targetlocalizationortargetshootingtasks. 1.3. The$present$study$ Thepresentstudyaimedatinvestigatingthejointinfluencesofbackgroundlateralmotionandvisual complexityonasimpleshootingtasksuchaswhatcanbefoundinvideogames.thegoalofthe shootingtaskusedintheexperimentswastoaimandshootasfastaspossibleatdifferentvisual targetsindicatedbyauditorycluestoobtainthebestscorepossible.thefirsthypothesiswasthatthe performanceislowerwhenthebackgroundisvisuallycomplexthanwhenitislesscomplexjie& Clark,2008;Wolfeetal.,2002).Becausepreviousstudiesshowedthatbackgroundmotionalso impairedperformanceintargetdetectiontaskscarouxetal.,2013;harrisonetal.,2010;kaminiarz etal.,2007;tozzietal.,2007),theperformanceimpairmentinducedbyvisualcomplexityshould interactwiththeimpairmentcausedbybackgroundmotion.thus,thesecondhypothesiswasthat theperformanceismoreimpairedbybackgroundcomplexitywhenthebackgroundismovingthan whenitisstatic.thesehypothesesweretestedintwosimilarexperiments.theonlydifference betweentheexperimentswasthenatureofthevisualelementsusedtodesignthebackground.the findingswereexpectedtobethesamewhateverthebackgroundvisualdisplay. 6

2. Experiment$1$ 2.1. Method$ 2.1.1. Participants$ TwentyWtwovolunteers16women,6men)tookpartintheexperiment.Theiraverageagewas19.9 yearssd=1.8)andtheiraveragelengthofschooling13.6yearssd=1.4).allparticipantswere nativefrenchspeakersandhadnormalorcorrectedwtownormalvision. 2.1.2. Apparatus$ AnonWinvasive,headWfree TobiiT120 eyewtrackerthatlookedlikea17 TFTcomputerscreen1280 x1024pixelsresolution)wasusedtomimicasmuchaspossiblenaturalinteractionwithavirtual environment.theeyetrackerwascontrolledviaacomputer,whichcollectedthedataandranthe taskprogram.gazepositionswereobtainedata120hzfrequencywithanaverageprecisionof0.5 degreeofvisualangleabout5mmonthescreen).becausethelaterallymovingbackgroundsusedin theexperimentsmovedleftwardsatabout12deg/sseebelow),thedatamayincludeoknslow phasesduringwhichtheacquisitionofinformationisstillongoingeventhoughtheobserver sgazeis movingrightwardsatthesamevelocity.hence,eyefixationsandsaccadesweredetectedusing velocitywbaseddetectionalgorithmsfromthe GazeAlyze softwareberger,winkels,lischke,& Höppner,2012).Fixationsweredefinedasanyperiodwheregazevelocitywaslessthan14deg/sfor atleast60ms.saccadesweredefinedasanyperiodwheregazevelocitywentover30deg/sformore than35ms.aspeakerthatwaslocatedinfrontofparticipantswithoutbiasofspatiallocation)was usedtodisplaysounds. 7

2.1.3. Material$ Thematerialwascreatedwith AdobeDirector11 software.threedifferentbackgroundsofvarious visualcomplexitiesweredesignedfigure1).theywereextractedfromthevideogame Childof Eden Ubisoft,2011)andwerecomposedofamainlygreenneutralpatternmainHSVcolorscale: Hue=120,Saturation=100,Value=10to70)scatteredwithabstractobjectsHSV:120,50W100,40W 100).Thecomplexitywasdeterminedaccordingtotheproportionofthebackgroundcoveredbythe objects,whichrepresentedtheclutter.thefirstversiononlyshowedtheneutralpatternnoclutter), thesecondoneshowedtheneutralpatternwithobjectscovering25%ofitssurfacelowclutter),and inthethirdonetheobjectscovered50%ofthebackgroundsurfacehighclutter).asstatedabove, whenthebackgroundwaslaterallymoving,itmovedleftwardsataspeedof121mm/sabout12 deg/s).thetargetandthedistractoroftheshootingtaskweredrawingsofacreature.fourcreature versionswereused.thecreaturecouldbebluehsv:228,74,25w84)orredhsv:7,74,25w84),and small85x66pixels,22x17mm,2,2x1,7degrees)orlarge85x99pixels,22x26mm,2.2x2.6degrees). Thecursorwasarepresentationofacrosshairof114pixelsdiameter30mm,3degrees).Six auditoryclueswererecordedwithamalenaturalvoice.theseclueswere left, right, blue, red, large and small gauche, droite, bleu, rouge, grand and petit infrench).their durationwas0.5second. [Figure1nearhere] 2.1.4. Design$and$procedure$ Thebackgroundcomplexityno,loworhighclutter)andmotionpresenceorabsence)were manipulatedwithinwparticipants. 8

Ashootingtaskwasused.Atthebeginningofeachtrial,thebackgroundwasdisplayedandanempty blacksquareof74mmsideabout7.4deg)wastransientlysuperimposedatthecentreofthescreen for1secondtoorienttheparticipant sgazetowardsthecentreofthedisplaywithoutcancellingthe effectsofbackgroundmotionsuchastheokn.participantswereinstructedtokeeptheirgazeas muchaspossiblewithinthesquare.theauditorycluewasdisplayedatthesametimethanthe square.thecluecouldbealocationclue left or right ),acolorclue blue or red )orasizeclue large or small ).Thetarget,thedistractorandthecursorappearedonthescreenallonthesame, randomhorizontalline.thecursorwasalwaysonthecentralverticalaxisofthescreen,whereasthe targetwasdisplayedrandomlyontherightorleftsideofthescreen.thehorizontalcoordinateof appearanceofthetargetbetweenthecursorandthescreenside)wasalsorandomlydetermined. Thedistractorwaslocatedattheexactoppositeofthetargetontheothersideofthescreencentral verticalaxis.thesizeandcolorofthedistractordifferedfromthetargetonlyonthevisualfeature thatcorrespondedtothenatureoftheclue.forexample,ifthecluewas red,thetargetwas necessarilyredbutcouldbelargeorsmall.thedistractorwasoftheoppositecolorhereblue)but hadthesamesizeasthetarget.participantshadtoaimatthetargetwiththehelpofthekeyboard buttons leftarrow and rightarrow,andtoshootatitbypushingthe space bar.participants wereabletomovethecursorandshootasoftenastheywishedwhilethetargetwasmissed,in otherwordswhilethecursorandthetargetwerenotsuperimposedatthetimeofshooting.when thetargetwashit,anothertrialbegan. Theexperimenterpresentedthisproceduretotheparticipantsasavideogame.Theywereaskedto touchasfastaspossibleeachtargetbyneglectingthedistractor.eachsetoftrialswaspresentedto theparticipantasonegame.sixgamesofsixtytrialswerepresentedtoeachparticipant,witha pausebetweeneachgame.theglobalscorewasgivenattheendofallblocks.alltrialsofeachgame wereperformedonthesamebackground,whichdidnotdisappearbetweeneachtrial.whenthe backgroundwasmoving,themotionwascontinuousanddidnotstopforthewholegame.theorder ofpresentationofthe6games2x3differentconditionsofmotionpresence/absenceand 9

complexity)perparticipantwaspseudowrandomized.ineachgame,theorderofpresentationofthe differentclueswasalsopseudowrandomized. 2.1.5. Dependent$measures$ Performancewasassessedusingthemeanresponsetimetohiteachtargetortocompleteeach trial)asthedependentmeasure.toexplaintheperformance,participants eyemovementswere analyzedusingsixdependentmeasures:themeannumberoffixationspertrial,themeandurationof fixations,theaveragelocationoffixationsonthedisplaydefinedbythehorizontal X andvertical Y coordinates),themeannumberofsaccadespertrialandtheaverageamplitudeofsaccades. Foreachtrial,onlytheeyefixationsandsaccadesthatweremadewhilesearchingforthetarget.In otherwords,boththefixationthatwasinterruptedbytheappearanceofthetargetanddistractor andthefixationthatwasongoingwhenthetargetwashitwerenotincludedintheanalysis.all variableswereanalyzedusingrepeatedmeasuresanovaswiththebackgroundmotionandthe backgroundcomplexityaswithinwparticipantsfactors.whenthemauchleysphericitytestwas significant,greenhousewgeissercorrectionwasapplied. 2.2. Results$ Alllateresponsesresponsetimesgreaterthan3000ms)wereexcludedfromanalyses.Thenumber oftrialsthatwereexcludedrepresentedonaverage2.1%ofthetotalnumberoftrialsperparticipant min=0.0%,max=13.3%).responsetimedatawerelogarithmicallytransformedbeforeanovas wereperformed.forclarityofpresentation,themeansoftheuntransformeddataarereportedin thetext,graphicandtable.themeansandstandarddeviationsofalldependentmeasuresare displayedintable1.theresultsoftheanovasandplannedcomparisonsthatwereperformedto analyzethedataaredisplayedintable2. 10

[Table1nearhere] [Table2nearhere] 2.2.1. Mean$response$time$ AsshownonFigure2,backgroundcomplexityhadaninfluenceontheresponsetime.Planned comparisonsdemonstratedthattheresponsetimewaslongerinthelowclutterconditionm=1392 ms,sd=264)thaninthenoclutterm=1341ms,sd=253),orhighclutterconditionsm=1359ms, SD=265).Thedifferencebetweenthesetwolastconditionswasnotsignificant.Backgroundmotion hadalsoanimpactontheresponsetime.theresponsetimewaslongeronthemovingbackground M=1404ms,SD=244)thanonthestaticoneM=1324ms,SD=272).However,theinteraction betweenthemotionandcomplexityfactorswasnotsignificant. [Figure2nearhere] 2.2.2. Eye$movement$data$ Qualitativeobservationoftheeyemovementdatadisplayedbyasampleofparticipantsshowedthat whenthebackgroundwasmoving,anoknconsistingofslowphasesorientedleftwardsinterrupted byquickphasesorientedrightwardswaspresentinbetweentrials.themaximumvelocityofslow phasesreached5to10deg/sdependingonparticipants.whenthetargetanddistractorappeared, theokndisappeared,andonlyfixationsandsaccadeswerevisible,probablybecausethetarget and/ordistractorwereusedasstationary anchoringpoints tocancelthenystagmusilg,1997). 11

Asexplainedinthemethodsection,onlytheeyefixationsandsaccadesthatweremadewhile searchingforthetargetwereanalyzed.hence,thefixationsandsaccadesthatwereanalyzed accountedforabout50%ofresponsetimes. Fixations, Inaccordancewiththeresponsetimedata,backgroundcomplexityhadaninfluenceonthenumber offixationsthatweremadewhilesearchingforthetarget.plannedcomparisonsdemonstratedthat thenumberoffixationswashigherinthelowclutterconditionthaninthenoclutterone.other comparisonswerenotsignificant,eventhoughparticipantstendedtomakemorefixationsinthelow clutterconditionthaninthehighclutterone.backgroundmotionhadalsoanimpactonthenumber offixations,whichwashigheronthemovingbackgroundthanonthestaticone.however,the interactionbetweenthetwofactorswasnotsignificant. BackgroundmotionhadanimpactonthehorizontalcoordinateX)offixations.Inaverage,fixations werelocatedmorerightwardsonthemovingbackgroundthanonthestaticone.background complexityhadnoimpactonthehorizontalcoordinateoffixations,buttheinteractionbetweenthe twofactorswassignificant.plannedcomparisonsdemonstratedthatwhenthebackgroundwas moving,thefixationswerelocatedmorerightwardsinthehighclutterconditionthaninthelow clutterone,andalsomorerightwardsinthelowclutterconditionthaninthenoclutterone.when thebackgroundwasstatic,incontrast,therewasnotanysignificanteffectofbackgroundcomplexity onthehorizontalcoordinateoffixations. Therewasnotanysignificanteffectofbackgroundcomplexityormotiononthemeandurationor theverticalcoordinatey)ofthefixations,oranysignificantinteractionbetweenthetwofactors. Saccades, Thenumberofsaccadesmadebytheparticipantswhilesearchingforthetargetwashigher,and theiraverageamplitudelower,onthemovingbackgroundthanonthestaticone.therewasnotany 12

significanteffectofbackgroundcomplexityonthemeannumberortheaverageamplitudeof saccades,oranysignificantinteractionbetweenthetwofactors. 3. Experiment$2$ 3.1. Method$ Theapparatus,design,procedureandparticipantsofExperiment2werethesameasthoseof Experiment1.ThematerialwasthesameasinExperiment1,butthethreebackgroundswere extractedfromthevideogame SimCity4 ElectronicArts,2003)Figure1),andwerecomposedof amainlygreenneutralpatternscatteredhsv:75,30w50,30)withnaturalisticobjectshsv:75,0w50, 20). 3.2. Results$ Asinexperiment1,alllateresponsesresponsetimesgreaterthan3000ms)wereexcludedfrom analyses.thenumberoftrialsthatwereexcludedrepresentedonaverage2.0%ofthetotalnumber oftrialsperparticipantmin=0.0%,max=10.8%).responsetimedatawerelogarithmically transformedbeforeanovaswereperformed.forclarityofpresentation,themeansofthe untransformeddataarereportedinthetext,graphicandtable.themeansandstandarddeviations ofalldependentmeasuresaredisplayedintable3.theresultsoftheanovasandplanned comparisonsthatwereperformedtoanalyzethedataaredisplayedintable4. [Table3nearhere] [Table4nearhere] 13

3.2.1. Mean$response$time$ AsshownonFigure3,backgroundcomplexityhadnotanysignificantinfluenceontheresponsetime. Incontrast,backgroundmotionhadanimpactontheresponsetime,whichwaslongeronthe movingbackgroundm=1360ms,sd=262)thanonthestaticonem=1291ms,sd=250). Furthermore,theinteractionbetweenbackgroundmotionandcomplexitywassignificant.Planned comparisonsshowedthatwhenthebackgroundwasmoving,theresponsetimewaslongerinthe lowclutterconditionthaninthenoclutterone.othercomparisonswerenotsignificant.whenthe backgroundwasstatic,theresponsetimewasnotsignificantlydifferentbetweenthethreeclutter conditions. [Figure3nearhere] 3.2.2. Eye$movement$data$ AsinExperiment1,qualitativeobservationoftheeyemovementdatadisplayedbyasampleof participantssuggestedthatwhenthebackgroundwasmoving,anoknwastriggeredinbetween trials.again,onlytheeyefixationsandsaccadesthatweremadewhilesearchingforthetargetwere analyzed.theyaccountedforabout40%ofresponsetimes. Fixations, Eventhoughparticipantstendedtomakemorefixationswhenthebackgroundwasmoving,there wasnotanysignificanteffectofbackgroundcomplexityormotiononthemeannumberoffixations thatweremadewhilesearchingforthetarget,oranysignificantinteractionbetweenthetwo factors. 14

Similarly,therewasnotanysignificanteffectofbackgroundcomplexityormotiononthemean durationortheverticalcoordinatey)ofthefixations,oranysignificantinteractionbetweenthetwo factors AsinExperiment1,backgroundmotionhadanimpactonthehorizontalcoordinateX)offixations. Thefixationswerelocatedmorerightwardsonthemovingbackgroundthanonthestaticone.In contrast,therewasnotanysignificanteffectofbackgroundcomplexityonthehorizontalcoordinate offixations,oranysignificantinteractionbetweenthetwofactors. Saccades, AsinExperiment1,theaverageamplitudeofsaccadeswasloweronthemovingbackgroundthanon thestaticone.but,incontrast,therewasnotanysignificanteffectofbackgroundmotiononthe meannumberofsaccades.therewasnotanysignificanteffectofbackgroundcomplexityonthe meannumberortheamplitudeofsaccades,oranysignificantinteractionbetweenthetwofactors. 4. Discussion$ Thefirsthypothesiswasthattheperformanceislowerwhenthebackgroundiscomplexthanwhenit islesscomplex.itwaspartiallysupported.theresponsetimevariedsignificantlyaccordingtothe backgroundcomplexityonlyinexperiment1.furthermore,theresponsetimewashigherinthelow clutterconditionthaninboththenoclutterandhighclutterconditions.inaccordancewiththese data,participantsmademoreortendedtomakemorefixationswhilesearchingforthetargetinthe lowclutterconditionthaninthenoclutterorhighclutterconditions.accordingtobecketal.2010) andwolfeetal.2002),theperformanceimpairmentinavisualsearchtaskwouldlinearlyincrease withthevisualcomplexityofthescene.thus,theparticipants responsetimeshouldhavebeen higherinthehighclutterthaninthelowcluttercondition.hencethewaythevisualcomplexityof backgroundswassetinthepresentstudymaynothavebeencompletelyadequate.accordingtothe results,thepresenceofobjectssuperimposedonapatterndoesincreasethevisualcomplexityofthe 15

background,butincreasingtheproportionofthesurfacetheycoverdoesnotseemtoincrease backgroundcomplexity,andmayactuallydecreaseit.thequantityofsalientvisualcontrastsinthe backgroundmaynotdirectlydependontheproportionofthescenecoveredbytheobjects. Inordertohaveanothermeasurethanthelevelofcluttertoqualifythecomplexityofeach backgroundusedinthepresentstudy,saliencymapswerecomputedfromthevariousbackgrounds usedinthetwoexperimentsusingthe Saliencytoolbox2.3 Walther&Koch,2006),which implementsthesaliencymodeloriginallyproposedbyittiandkoch2000)figure4).thismodelis abletopredicthumangazeallocationonthedifferentpartsofvisualscenesbycomputingregionsof saliency.intheresultantsaliencymaps,lowvaluesindicatetheregionsofthescenethatarenot salient,whereashighvaluesindicatetheregionsthataresalientandtendtoattracttheobserver s attention. QualitativeobservationofthesaliencymapsobtainedforthebackgroundsusedinExperiment1 showthattherewereseveralhighlysalientregionsinthelowclutterbackground,whereasthe overallsaliencyofsalientregionswaslowerinthenoclutterandhighclutterbackgrounds. Consequently,theparticipants gazewasprobablymoreimpactedbylowwlevelvisualfeaturesinthe lowclutterbackgroundthanintheotherones.thisisinaccordancewithresponsetimedata,which demonstratedthatperformancewasmoreimpairedbythelowclutterbackgroundthanbythehigh clutterone. ThesaliencymapsobtainedforthebackgroundsusedinExperiment2werequitesimilartothose obtainedinexperiment1,i.e.displayedmorehighlysalientregionsinthelowclutterconditionthan inthetwootherones.however,thedifferencebetweenthethreetypesofbackgroundwasless importantthaninexperiment1.thiscouldexplainwhytheparticipants gazeandperformancewere notsignificantlyimpactedbymanipulationsofbackgroundcomplexity,butonlybythejoint manipulationofbothbackgroundmotionandcomplexity. 16

[Figure4nearhere] Insum,inthesetwoexperiments,themostvisuallycomplexbackgroundwasapparentlythatwhere thesuperimposedobjectscovered25%,andnot50%,ofthescreensurface.whentheproportionof thescreencoveredbyobjectswastoohigh,theimpactofthebackgroundwasnotsignificantly differentfromthatofthebasicbackgroundwherenoobjectwaspresent.hence,thesaliencyscale ofavisualsceneseemstogiveabettermeasureofcomplexitythanthelevelofclutter,but complementaryexperimentsareneededtodeterminetowhatextentthisistrue. ContrarytowhatwasexpectedaccordingtoHendersonetal.2009),theanalysisofeyemovements didnotdemonstrateanysignificantinfluenceofbackgroundcomplexityonthedurationofeye fixations.thisconfirmsthattheproportionofthescenecoveredbyobjectsmaynotbeanideal measureofbackgroundcomplexity.alternatively,theinfluenceofthisfactoronthedurationof fixationsmaybetooweakinthepresentconditionstobeobservable. Thesecondhypothesiswasthatwithacomplexbackground,theperformanceisevenmoreimpaired when,inaddition,thebackgroundismoving.itwaspartiallysupported.theresultsshowedthatthe performancewasalwayslowerwhenthebackgroundwasmovingthanwhenitwasstatic,whatever thetypeofbackground.theseresultsareinlinewiththoseofpreviousstudiescarouxetal.,2013; Harrisonetal.,2010;Kaminiarzetal.,2007;Tozzietal.,2007).Theanalysisofeyemovements showedthatthisimpairmentmaybeduetotheneedtocanceltheokntriggeredbybackground motion,whichwoulddisturbgazecontrolandinformationprocessingwhiletheparticipantsare searchingforandshootingatthetarget.indeed,whenthebackgroundwasmoving,theaveragegaze orientationwasdeviatedtowardsthesideoforiginofthemotionasexpectedinthepresenceofokn Ilg,1997).Inaddition,participantsmadesmallersaccadesinbothexperimentsandtendedtomake moresaccadesandfixationsonthedisplay,thoughsignificancewasreachedonlyinexperiment1. 17

Contrarytopredictions,however,thepredictedinteractionbetweenthebackgroundmotionand complexitywassignificantonlyinexperiment2.theresultsshowedthatwhentherewasnoclutter orahighclutter,therewasnotanysignificantdifferenceofresponsetimebetweenthestaticand movingbackgrounds.whentheclutterwaslow,theresponsetimewashigheronthemoving backgroundthanonthestaticone.inthisexperiment,thepresenceofobjectssuperimposedonthe neutralpatternimpairedperformanceonlywhenthebackgroundwasmoving,andonlywhenthe proportionofthebackgroundsurfacecoveredbyobjectswasnottoohighi.e.whenthebackground includednumeroushighlysalientregions). 4.1. Conclusions$and$outlook$ Thepresentstudyshowedthattheperformanceinasimpleshootingtaskisoftenimpairedby backgroundmotion,inaccordancewithpreviousstudieswithothertaskscarouxetal.,2013; Harrisonetal.,2010;Kaminiarzetal.,2007;Tozzietal.,2007).Moreover,thepresentstudy demonstratedthattheeffectsofbackgroundvisualcomplexityandmotionontheperformanceare additiveforoneofthebackgroundsexperiment1)andmultiplicativefortheotheroneexperiment 2). However,onelimitofthepresentstudyisthatthetwoexperimentsdidnotgiveexactlythesame results.theimpactofbackgroundcomplexityonparticipants performancewasdifferentaccording tothebackgroundthatwasused.inexperiment1,thesimpleeffectofbackgroundcomplexitywas significant.inexperiment2,thesimpleeffectofbackgroundcomplexitywasnotsignificant,butthere wasasignificantinteractionwithbackgroundmotionsuchthatbackgroundcomplexityhada significantimpactonperformancewhenthebackgroundwasmoving. Thisdifferenceofresultscanonlybeduetothenatureofthevisualelementsthatwereusedinthe twobackgrounds.allotherparametersoftheexperimentswerestrictlysimilar.amongpossible explanations,thedifferentarrangementsoftheobjectsontheneutralpattern,orthedifferent 18

shadesofgreensusedforthepatterns,theobjectsorbothseemtocreatedifferentialcontrastsand localcomplexitiesbetweenthetwobackgrounds.inaddition,thecolorsofthedifferentvisual elementsusedinthetwobackgroundsweredifferentintermsofcolorhue,saturationand value.allthismayinfluencethedifficultyofthetargetanddistractorperceptiontask.forexample, previousstudiesshowedthatvisualsearchperformancemayvarydependingonothertypesofloww levelfeaturesofthebackground,suchasluminance,orientationandspatialfrequencye.g.,devries, Hooge,Wertheim,&Verstraten,2013).Furtherexperimentsarenecessarytoexplaintowhatextent thesespecificlowwlevelfeaturescaninfluencetheperceptionanduseofobjectssuperimposedona structuredbackground,incombinationwithbackgroundcomplexityandmotion. 5. Acknowledgments$ TheauthorsthankJeanPylousterforhistechnicalassistanceintheanalysisoftheeyemovement data,especiallyintheadaptationofthe GazeAlyze softwarepackageforthetobiit120data.loïc CarouxwassupportedbyaPh.D.fellowshipfromtheDirectionGénéraledel ArmementDGA, FrenchMinistryofDefense)andfollowedintheframeofthisfellowshipbyDidierBazalgette. 6. References$ Asher,M.F.,Tolhurst,D.J.,Troscianko,T.,&Gilchrist,I.D.2013).Regionaleffectsofclutteron humantargetdetectionperformance.journalofvision,135),article25,1 15. doi:10.1167/13.5.25 Beck,M.R.,Lohrenz,M.C.,&Trafton,J.G.2010).Measuringsearchefficiencyincomplexvisual searchtasks:globalandlocalclutter.journalofexperimentalpsychology:applied,16,238 250.doi:10.1037/a0019633 Berger,C.,Winkels,M.,Lischke,A.,&Höppner,J.2012).GazeAlyze:aMATLABtoolboxforthe 19

analysisofeyemovementdata.behaviorresearchmethods,44,404 419. doi:10.3758/s13428w011w0149wx Caroux,L.,LeBigot,L.,&Vibert,N.2013).Impactofthemotionandvisualcomplexityofthe backgroundonplayers performanceinvideogamewlikedisplays.ergonomics,56,1863 1876. doi:10.1080/00140139.2013.847214 Chen,X.,&Hegdé,J.2012).Learningtobreakcamouflagebylearningthebackground.Psychological Science,23,1395 1403.doi:10.1177/0956797612445315 DeVries,J.P.,Hooge,I.T.C.,Wertheim,A.H.,&Verstraten,F.A.J.2013).Background,animportant factorinvisualsearch.visionresearch,86,128 138.doi:10.1016/j.visres.2013.04.010 Harrison,W.J.,Thompson,M.B.,&Sanderson,P.M.2010).MultisensoryintegrationwithaheadW mounteddisplay:backgroundvisualmotionandsoundmotion.humanfactors,52,78 91. doi:10.1177/0018720810367790 Henderson,J.M.,Chanceaux,M.,&Smith,T.J.2009).TheinfluenceofclutteronrealWworldscene search:evidencefromsearchefficiencyandeyemovements.journalofvision,91),article32, 1 8.doi:10.1167/9.1.32 Honda,H.2001).Visualmislocalisationinducedbytranslationalandradialbackgroundmotion. Perception,30,935 944.doi:10.1068/p3132 Ilg,U.J.1997).Sloweyemovements.ProgressinNeurobiology,53,293 329.doi:10.1016/S0301W 008297)00039W7 Itti,L.,&Koch,C.2000).AsaliencyWbasedsearchmechanismforovertandcovertshiftsofvisual attention.visionresearch,40,1489 1506. Jie,L.,&Clark,J.J.2008).VideogamedesignusinganeyeWmovementWdependentmodelofvisual attention.acmtransactionsonmultimediacomputingcommunicationsandapplications, 20

43),article22,1 16.doi:10.1145/1386109.1386115 Kaminiarz,A.,Krekelberg,B.,&Bremmer,F.2007).Localizationofvisualtargetsduringoptokinetic eyemovements.visionresearch,47,869 878.doi:10.1016/j.visres.2006.10.015 Kim,J.,&Palmisano,S.2010).Eccentricgazedynamicsenhancevectionindepth.JournalofVision, 1012),article7,1 11.doi:10.1167/10.12.7 Neider,M.B.,&Zelinsky,G.J.2011).Cuttingthroughtheclutter:Searchingfortargetsinevolving complexscenes.journalofvision,1114),article7,1 16.doi:10.1167/11.14.7 Rayner,K.2009).Eyemovementsandattentioninreading,sceneperception,andvisualsearch. QuarterlyJournalofExperimentalPsychology,62,1457 1506. doi:10.1080/17470210902816461 Riecke,B.E.,SchulteWPelkum,J.,Avraamides,M.N.,VonDerHeyde,M.,&Bülthoff,H.H.2006). CognitivefactorscaninfluenceselfWmotionperceptionvection)invirtualreality.ACM TransactionsonAppliedPerception,3,194 216.doi:10.1145/1166087.1166091 Tozzi,A.,Morrone,M.C.,&Burr,D.C.2007).Theeffectofoptokineticnystagmusontheperceived positionofbrieflyflashedtargets.visionresearch,47,861 868. doi:10.1016/j.visres.2006.10.022 Trutoiu,L.C.,Mohler,B.J.,SchulteWPelkum,J.,&Bülthoff,H.H.2009).Circular,linear,and curvilinearvectioninalargewscreenvirtualenvironmentwithfloorprojection.computers& Graphics,33,47 58.doi:10.1016/j.cag.2008.11.008 Waespe,W.,&Schwarz,U.1987).Sloweyemovementsinducedbyapparenttargetmotionin monkey.experimentalbrainresearch,67,433 435.doi:10.1007/bf00248564 Walther,D.,&Koch,C.2006).ModelingattentiontosalientprotoWobjects.NeuralNetworks,19, 1395 1407.doi:10.1016/j.neunet.2006.10.001 21

Wolfe,J.M.1994).GuidedSearch2.0:Arevisedmodelofvisualsearch.PsychonomicBulletin& Review,1,202 238.doi:10.3758/bf03200774 Wolfe,J.M.,Oliva,A.,Horowitz,T.S.,Butcher,S.J.,&Bompas,A.2002).Segmentationofobjects frombackgroundsinvisualsearchtasks.visionresearch,42,2985 3004.doi:10.1016/S0042W 698902)00388W7 22

Table1.MeansM)andstandarddeviationsSD)ofdependentmeasuresaccordingtobackground complexityandmotioninexperiment1. Noclutter Lowclutter Highclutter M SD M SD M SD Meanresponsetimeinms) Staticbackground 1298 262 1375 292 1299 257 Movingbackground 1384 237 1409 234 1419 262 Meannumberoffixations Staticbackground 1.61 0.63 1.96 1.09 1.64 0.71 Movingbackground 1.98 0.86 2.11 0.91 2.06 0.98 Meandurationoffixationsinms) Staticbackground 258 114 235 84 274 103 Movingbackground 253 97 234 79 250 77 Averagepositionoffixationsinpixels) Horizontal*coordinate*X)* Staticbackground 632 49 631 53 626 46 Movingbackground 642 41 658 43 674 57 Vertical*coordinate*Y)* Staticbackground 494 47 476 51 477 50 Movingbackground 489 51 490 46 495 37 Meannumberofsaccades Staticbackground 2.13 0.48 2.36 0.54 2.18 0.60 Movingbackground 2.49 0.60 2.60 0.62 2.55 0.83 Averageamplitudeofsaccadesindegrees) Staticbackground 5.35 0.83 5.02 0.77 5.06 0.56 Movingbackground 4.84 0.68 4.88 0.63 4.81 0.56 23

Table2.ResultsofANOVAsandplannedcomparisonsperformedinExperiment1. ANOVA Plannedcomparison df* F@ratio p@value η 2 p* Meanresponsetime BackgroundComplexity 2,42 4.87 <.05.19 Novs.Low 1,21 7.66 <.05 W Novs.High 1,21 1.02.32 W Lowvs.High 1,21 4.90 <.05 W BackgroundMotion 1,21 32.08 <.001.60 BackgroundComplexityxMotion 2,42 2.08.14 W Meannumberoffixations BackgroundComplexity 2,42 3.89 <.05.16 Novs.Low 1,21 7.24 <.05 W Novs.High 1,21 0.57.46 W Lowvs.High 1,21 3.02.10 W BackgroundMotion 1,21 7.57 <.05.27 BackgroundComplexityxMotion 2,42 1.41.26 W Meandurationoffixations BackgroundComplexity 2,42 2.22.12 W BackgroundMotion 1,21 0.71.41 W BackgroundComplexityxMotion 2,42 0.68.51 W Averagepositionoffixations Horizontal*coordinate*X)* BackgroundComplexity 2,42 3.38.06 W BackgroundMotion 1,21 48.34 <.001.70 BackgroundComplexityxMotion 2,42 6.37 <.01.23 Static,Novs.Low 1,21 0.04.84 W Static,Novs.High 1,21 0.50.49 W Static,Lowvs.High 1,21 0.74.40 W Moving,Novs.Low 1,21 6.69 <.05 W Moving,Novs.High 1,21 26.27 <.001 W Moving,Lowvs.High 1,21 5.07 <.05 W Vertical*coordinate*Y)* BackgroundComplexity 2,42 0.57.57 W BackgroundMotion 1,21 2.33.14 W BackgroundComplexityxMotion 2,42 2.38.11 W Meannumberofsaccades BackgroundComplexity 2,42 2.76.08 W BackgroundMotion 1,21 18.24 <.001.47 BackgroundComplexityxMotion 2,42 0.47.63 W Averageamplitudeofsaccades BackgroundComplexity 2,42 1.68.20 W BackgroundMotion 1,21 10.93 <.01.34 BackgroundComplexityxMotion 2,42 2.32.11 W Note.No=NoClutter;Low=LowClutter;High=HighClutter;Static=StaticBackground;Moving=Moving Background.Plannedcomparisonsaredisplayedonlywhenthecorrespondingmaineffectorinteractionwas significant.partialη²aredisplayedonlywhenthemaineffectsorinteractionsweresignificant. 24

Table3.MeansM)andstandarddeviationsSD)ofdependentmeasuresaccordingtobackground complexityandmotioninexperiment2. Noclutter Lowclutter Highclutter M SD M SD M SD Meanresponsetimeinms) Staticbackground 1277 248 1276 258 1320 246 Movingbackground 1314 229 1412 297 1354 250 Meannumberoffixations Staticbackground 1.38 0.53 1.40 0.59 1.47 0.66 Movingbackground 1.50 0.56 1.44 0.65 1.60 0.80 Meandurationoffixationsinms) Staticbackground 236 113 247 125 211 86 Movingbackground 231 69 204 48 204 73 Averagepositionoffixationsinpixels) Horizontal*coordinate*X)* Staticbackground 644 55 633 64 628 60 Movingbackground 652 56 663 54 648 58 Vertical*coordinate*Y)* Staticbackground 470 77 498 53 479 59 Movingbackground 480 52 480 63 491 51 Meannumberofsaccades Staticbackground 1.87 0.63 1.81 0.76 1.95 0.82 Movingbackground 2.00 0.64 1.89 0.80 1.98 0.95 Averageamplitudeofsaccadesindegrees) Staticbackground 5.70 1.08 5.61 1.04 6.04 1.57 Movingbackground 5.23 0.98 5.70 1.05 5.51 1.36 25

Table4.ResultsofANOVAsandplannedcomparisonsperformedinExperiment2. ANOVA Plannedcomparison df* F@ratio p@value η 2 p* Meanresponsetime BackgroundComplexity 2,42 2.65.08 W BackgroundMotion 1,21 6.71 <.05.70 BackgroundComplexityxMotion 2,42 3.81 <.05.66 Static,Novs.Low 1,21 0.01.97 W Static,Novs.High 1,21 3.56.07 W Static,Lowvs.High 1,21 2.87.10 W Moving,Novs.Low 1,21 6.97 <.05 W Moving,Novs.High 1,21 1.88.18 W Moving,Lowvs.High 1,21 3.07.09 W Meannumberoffixations BackgroundComplexity 2,42 1.01.37 W BackgroundMotion 1,21 1.92.18 W BackgroundComplexityxMotion 2,42 0.32.73 W Meandurationoffixations BackgroundComplexity 2,42 1.40.26 W BackgroundMotion 1,21 1.76.20 W BackgroundComplexityxMotion 2,42 1.14.33 W Averagepositionoffixations Horizontal*coordinate*X)* BackgroundComplexity 2,42 0.86.43 W BackgroundMotion 1,21 20.36 <.001.49 BackgroundComplexityxMotion 2,42 1.55.22 W Vertical*coordinate*Y)* BackgroundComplexity 2,42 2.00.15 W BackgroundMotion 1,21 0.03.87 W BackgroundComplexityxMotion 2,42 1.74.19 W Meannumberofsaccades BackgroundComplexity 2,42 0.90.41 W BackgroundMotion 1,21 0.96.34 W BackgroundComplexityxMotion 2,42 0.30.74 W Averageamplitudeofsaccades BackgroundComplexity 2,42 2.20.12 W BackgroundMotion 1,21 6.05 <.05.22 BackgroundComplexityxMotion 2,42 2.29.11 W Note.No=NoClutter;Low=LowClutter;High=HighClutter;Static=StaticBackground;Moving= MovingBackground.Plannedcomparisonsaredisplayedonlywhenthecorrespondingmaineffector interactionwassignificant.partialη²aredisplayedonlywhenthemaineffectsorinteractionswere significant. 26

Experiment1 Experiment2 No clutter Backgroundcomplexity Low clutter High clutter Figure1.BackgroundsusedinExperiment1andExperiment2,withdifferentexamplesoflocationsofatarget, adistractorandthecursor.foreachexperiment,threebackgroundsofvariouscomplexitiesweredesigned. Thecomplexitywasdeterminedbytheclutter,i.e.theproportionoftheinitial,neutralpatterncoveredbythe superimposedobjects. 27

MeanresponseFmems) 2200 2000 1800 1600 1400 1200 1000 Movingbackground Stazcbackground 800 700 0 Nocluyer Lowcluyer Highcluyer Backgroundcomplexity Figure2.Meanresponsetimeinms)tohiteachtargetineachconditionofbackgroundcomplexityandmotion inexperiment1,representedonalogarithmicallyspacedaxis.theerrorbarsrepresent±1standarderrorofthe mean. 28

MeanresponseFmems) 2200 2000 1800 1600 1400 1200 1000 Movingbackground Stazcbackground 800 700 0 Nocluyer Lowcluyer Highcluyer Backgroundcomplexity Figure3.Meanresponsetimeinms)tohiteachtargetwithineachconditionofbackgroundcomplexityand motioninexperiment2,representedonalogarithmicallyspacedaxis.theerrorbarsrepresent±1standard errorofthemean. 29

!! Experiment!1! Abstractbackground Experiment!2! Correspondingsaliencymap Correspondingsaliencymap Naturalisticbackground No clutter Background!Complexity! Low clutter High clutter Figure'4.BackgroundsusedinExperiments1and2withthecorrespondingsaliencymaps.Thebrighterregionswithinthesaliencymapsindicatehigher valuesofsaliency. 30