Craniofacial identification PDF
Preview Craniofacial identification
fi Craniofacial Identi cation ThepromotionofCCTVsurveillanceandidentitycards,alongwithever-heightenedsecurityat airports,immigrationcontrolandinstitutionalaccess,hasseenadramaticincreaseintheuseof automatedandmanualrecognition.Inaddition,severalrecentdisastershavehighlightedthe problemsandchallengesassociatedwithcurrentdisastervictimidentification. Discussingthelatestadvancesandkeyresearchintoidentificationfromthefaceandskull,this bookdrawstogetherawiderangeofelementsrelatingtocraniofacialanalysisandidentification. Itexaminesallaspectsoffacialidentification,includingthedeterminationoffacialappearance fromtheskull,comparisonoftheskullwiththefaceandtheverificationoflivingfacialimages. Withsectionscoveringtheidentificationofthedeadandoftheliving,itprovidesavaluable reviewofthecurrentstateofplayalongwiththelatestresearchadvancesinthisconstantly evolvingfield. CarolineWilkinsonisProfessorinCraniofacialIdentificationattheCentreforAnatomyandHuman IdentificationattheUniversityofDundee.SheisanexpertinfacialanthropologyandauthorofForensic FacialReconstruction(CambridgeUniversityPress,2004). ChristopherRynnisaPostdoctoralResearcherattheCentreforAnatomyandHumanIdentificationatthe UniversityofDundee.Heisanexpertincraniofacialapproximation/reconstructionandanthropology,and inforensicimageenhancementandanalysis. Craniofacial Identification Edited by Caroline Wilkinson and Christopher Rynn CentreforAnatomyandHumanIdentification UniversityofDundee cambridge university press Cambridge,NewYork,Melbourne,Madrid,CapeTown, Singapore,SãoPaulo,Delhi,MexicoCity CambridgeUniversityPress TheEdinburghBuilding,CambridgeCB28RU,UK PublishedintheUnitedStatesofAmericabyCambridgeUniversityPress,NewYork www.cambridge.org Informationonthistitle:www.cambridge.org/9780521768627 ©CambridgeUniversityPress2012 Thispublicationisincopyright.Subjecttostatutoryexception andtotheprovisionsofrelevantcollectivelicensingagreements, noreproductionofanypartmaytakeplacewithoutthewritten permissionofCambridgeUniversityPress. Firstpublished2012 PrintedintheUnitedKingdomattheUniversityPress,Cambridge AcataloguerecordforthispublicationisavailablefromtheBritishLibrary LibraryofCongressCataloguinginPublicationdata Craniofacialidentification/editedbyCarolineWilkinsonandChristopherRynn. p. cm. Includesbibliographicalreferencesandindex. ISBN9780521768627(hardback) 1. Facialreconstruction(Anthropology) 2. Face–Identification. 3. Face–Imaging. 4. Biometric identification. I. Wilkinson,Caroline,1965– II. Rynn,Christopher. II. Title. GN74.C73 2012 599.9048–dc23 2011034917 ISBN9780521768627Hardback CambridgeUniversityPresshasnoresponsibilityforthepersistenceor accuracyofURLsforexternalorthird-partyinternetwebsitesreferredto inthispublication,anddoesnotguaranteethatanycontentonsuch websitesis,orwillremain,accurateorappropriate. Contents Listofcontributors pagevi fi Part I: Identi cation of the Living 13. Three-dimensionalfacialimaging 154 StephenRichmond,AlexeiZhurovandArshed 1. Familiarfacerecognition 1 Toma VickiBruce 2. Unfamiliarfacerecognition 11 fi Part II: Identi cation of the Dead PeterJ.B.Hancock 3. EFIT-V:Evolutionaryalgorithmsandcomputer 14. Post-mortempredictionoffacial composites 24 appearance 166 ChrisSolomon,StuartGibsonandMatthew CarolineWilkinsonandAmyTillotson Maylin 15. Manualforensicfacialreconstruction 184 4. Facialrecallandcomputercomposites 42 LudoVermeulen CharlieFrowd 16. Relationshipsbetweentheskull 5. Facialageing 57 andface 193 DavidHunter,BernardTiddemanandDavid ChristopherRynn,TatianaBaluevaandElizaveta Perrett Veselovskaya 6. Ageprogressionandregression 68 17. Automatedfacialreconstruction 203 JoeMullins DirkVandermeulen,PeterClaes,SvenDeGreef, GuyWillems,JohnClementandPaulSuetens 7. Computer-assistedageprogression 76 StuartGibson 18. Computer-generatedfacialdepiction 222 GregoryMahoneyandCarolineWilkinson 8. Facialrecognitionfromidentification parades 86 19. Craniofacialsuperimposition 238 CatrionaHavardandAminaMemon MineoYoshino 9. Virtualhumanidentificationline-ups 101 20. Juvenilefacialreconstruction 254 KathrynY.Segovia,JeremyN.Bailensonand CarolineWilkinson CarrieLeonetti 10. Computer-generatedfacemodels 115 BernardTiddeman Index 261 11. Recognisingandlearningfacesin motion 125 Thecolourplatesaretobefoundbetweenpages KarenLanderandNatalieButcher 88and89. 12. Facialimagecomparison 136 JoshP.Davis,TimValentineandCaroline Wilkinson v Contributors JeremyN.Bailenson PeterJ.B.Hancock VirtualHumanInteractionLab DepartmentofPsychology StanfordUniversity UniversityofStirling TatianaBalueva CatrionaHavard RussianAcademyofScience SchoolofPsychology UniversityofAberdeen VickiBruce SchoolofPsychology DavidHunter NewcastleUniversity SchoolofPsychology UniversityofStAndrews NatalieButcher SchoolofSocialSciencesandLaw KarenLander TeessideUniversity SchoolofPsychologicalSciences UniversityofManchester PeterClaes CentreforProcessingSpeechandImages CarrieLeonetti ESAT–PSI FutureHealthDepartment–IBBT GregoryMahoney KatholiekeUniversiteit,Leuven MatthewMaylin SchoolofPhysicalSciences&VisionmetricLtd JohnClement UniversityofKent,Canterbury DentalSchool UniversityofMelbourne AminaMemon RoyalHollowayUniversityofLondon JoshP.Davis DepartmentofPsychologyandCounselling JoeMullins UniversityofGreenwich Forensicartist SvenDeGreef DavidPerrett ForensicOdontology SchoolofPsychology DepartmentOralHealthServices UniversityofStAndrews KatholiekeUniversiteit,Leuven StephenRichmond CharlieFrowd DentalSchool UniversityofCentralLancashire CardiffUniversity StuartGibson ChristopherRynn SchoolofPhysicalSciences&VisionmetricLtd CentreforAnatomy&HumanIdentification,CLS UniversityofKent,Canterbury UniversityofDundee vi Listofcontributors KathrynY.Segovia DirkVandermeulen VirtualHumanInteractionLaboratory CentreforProcessingSpeechandImages StanfordUniversity ESAT–PSI FutureHealthDepartment–IBBT ChrisSolomon KatholiekeUniversiteit,Leuven SchoolofPhysicalSciences&VisionmetricLtd UniversityofKent,Canterbury LudoVermeulen Forensicartist PaulSuetens CentreforProcessingSpeechandImages ElizavetaVeselovskaya ESAT–PSI RussianAcademyofScience FutureHealthDepartment–IBBT CarolineWilkinson KatholiekeUniversiteit,Leuven CentreforAnatomy&HumanIdentification,CLS BernardTiddeman UniversityofDundee DepartmentofComputerScience GuyWillems AberystwythUniversity ForensicOdontology AmyTillotson DepartmentOralHealthServices CentreforAnatomyandHumanIdentification KatholiekeUniversiteit,Leuven UniversityofDundee MineoYoshino ArshedToma NationalResearchInstituteofPoliceScience DentalSchool Chiba,Japan CardiffUniversity AlexeiZhurov TimValentine DentalSchool DepartmentofPsychology CardiffUniversity Goldsmiths,UniversityofLondon vii fi Identi cation of the Living PartI Chapter Familiar face recognition 1 Vicki Bruce 1.1 Introduction also elaborate on the contrast between familiar and unfamiliarfacerecognition. Thetaskofthepoliceofficerinvestigatingacrime,or of the forensic anthropologist working with human 1.2 Familiar versus unfamiliar remains,istoestablishanidentityofacriminalorofa face recognition victim. This often involves working with images of faces–buildingacompositeimagefromthememory When police investigate crimes the identity of the ofawitnesstothecrime,seekingCCTVimagesofthe villain or villains is often unknown, and the police person or persons who might have committed the willquestionwitnesseswhomaybeaskedindifferent crime,orbuildingamodelofthefaceofanunknown waystoassistwithestablishingtheidentityofaperson person from their skull. Many of the chapters in this whowasunfamiliartothembeforethecriminalinci- volume describe the processes involved in such dent. When a witness to a crime is asked to try to reconstructions. identify the criminal from photographs or a line-up, Onceanimageofa faceisobtained,however,it ortobuildanimageofthefaceusingafacecomposite needs to be identified. TV programmes such as system, this is typically difficult and error-prone. In CrimewatchintheUK(seewww.bbc.co.uk/crimewatch) contrast,mostof usmanageto recognise thefacesof often display witness-generated facial composites or familiar people in our everyday lives or on the tele- CCTV images of people associated with crimes which vision or other media reasonably accurately, despite sometimes result in people volunteering new infor- the enormous variation shown between different mation; Richard Neave’s constructed image of the appearancesofthesameperson.Error-proneunfam- unidentifiedvictim115oftheLondonUnderground iliar face memory is transformed to a generally very tube station fire at Kings Cross in 1987 (Chambers reliableperformancewithknownfaces. 2007) was displayed widely in newspapers and post- There is some neuropsychological evidence that ers. CCTV images of the London ‘nail bomber’ in somewhatdifferent processesunderliethe recognition 1999 led to hundreds of responses, including one ofunfamiliarfacesandtherecognitionoffamiliarones. phonecallfromamanwhonamedaworkcolleague, ‘Prosopagnosic’ people have difficulties recognising DavidCopeland,asresemblingtheimages.Thiscru- faces,sometimesasaresultofbraininjury.Theymay cialleadquicklyledtothearrestofDavidCopeland, beunabletorecogniseeventheirclosestrelativesfrom unfortunately not soon enough to prevent the third theirfaces,andeventheirownfaceinthemirrormay devastating bomb attack on The Admiral Duncan, a appear unfamiliar to them (see Harris and Aguirre, Londonpub. 2007, for a brief overview of this condition, and Whiletheproblemsofbuildingorusingimages DuchaineandNakayama,2006foroneofmanyrecent of unfamiliar faces are the subject of many other papersoncongenitalordevelopmentalprosopagnosia). chapters in this volume, here I focus on relevant Butsomeprosopagnosicpatientscanmanagetomatch issuesabouttheidentificationoffamiliarfaces,and images of unfamiliar faces, albeit using laborious and CraniofacialIdentification,ed.C.WilkinsonandC.Rynn.PublishedbyCambridgeUniversityPress. ©CambridgeUniversityPress2012. 1 V.Bruce sometimes time-consuming processes. Young and his memory system begins to weight the internal features colleagues (1993) investigated residual deficits in face more strongly. Consistent with this, Megreya and processinginagroupof34brain-injuredwarveterans. Bindemann(2009)showedthatwhenfacerecognition Amongst this group they found one man who was was tested in Egypt, adults, but not children, showed impairedonfamiliarfacerecognition,butunimpaired better memory for internal features for unfamiliar as at unfamiliar face matching, and another who was well as familiar faces, probably because the common- impaired on unfamiliar face matching but recognised place wearing of head scarves means that attention is familiar faces quite normally. This pattern of ‘double always oriented more towards internal than external dissociation’ is consistent with the idea that different featuresinthatculture. brain areas and/or processes are involved in the two Therelativeimportanceoftheinternalfeaturesofa tasksofrecognisingfamiliarfacesandmatchingunfa- familiarface,particularlytheeyes,hasimplicationsfor miliarones. the effectiveness of different kinds of disguises. Furtherevidenceforthedissociationbetweenfamil- The trueidentitiesof Batman,andThe LoneRanger, iar and unfamiliar face processing is the observation were effectively concealed by their wearing of masks thatfamiliarfacerecognitionseemstodependonrather covering their eyes, in addition to hats that covered different kinds of information from unfamiliar recog- their hair. Sunglasses and hats can allow celebrities nition. Lander and Butcher (Chapter 11) review work anonymityinacrowd. suggestingthatrepresentationsoffamiliarfacescapture Burton and his colleagues (2005) have suggested somethingabouttheircharacteristicpatternsofmotion that representations of familiar faces are built up by as well as static form. Even within static form, there simplyaveragingtogetherindividualinstancesofseen appeartobedifferentemphasesinthevisualrepresen- faces. The differential weightings of internal features tations of familiar and unfamiliar faces. Ellis et al. duringfamiliarisation,andforcultureswhereexternal (1979)firstdemonstratedthatunfamiliarfacerecogni- featuresarenotoftenviewed,willlikelyariseasaresult tionwasdominatedbytheexternalfeaturesoftheface, ofselectiveattentionweightingareasofthefacediffer- includingthehair.Peoplefinditverydifficulttorecog- ently. An averaging mechanism with the addition of nise once-viewed faces if their hair is concealed or selective weighting through attentional mechanisms changed.However,whenfacesarefamiliartheirinter- wouldallowtherepresentationofafacetodevelopin nal features are more important in their recognition. a way which allows the face to be well-recognised, This dominance of the external over internal features despite variations in expression and viewpoint which for unfamiliar faces has been much-replicated areextremelydetrimentaltorecognitionofunfamiliar (e.g. Young et al., 1985b) and it is found in tasks that faces(e.g.Bruce,1982).Burtonandhiscolleagueshave involve just matching unfamiliar faces without any shownthatpeoplearefastertorecognisefamiliarfaces memory load (Bruce et al., 1999). O’Donnell and when shown an average of 20 different photographic Bruce (2001), using newly familiarised faces, showed instances of them, than when shown individual inst- thatitseemedtobetheeyesinparticularthatbecame ances alone. Moreover, in an interesting practical betterrepresentedinrecentlyfamiliarisedfaces. extension of this work, Jenkins and Burton (2008) Why should representations of familiar faces showed that when an average of 20 instances of each becomeshiftedtowardsinternalandawayfromexter- ofasetoffamousfacetargetswasusedasaprobeto nalfeatures?Foranunfamiliarface,atleastinWestern matchagainstadatabaseofimagesofover3000celeb- Europewherehairisgenerallyvisibleandveryvariable rities, performance increased from 51% correct instyleandcolour,theouterfeaturesofthefaceprob- matching obtained from using individual image ably convey the most information that will be useful probes, to100%correctwhentheaverageswereused for matching and memory. As we see a face more asprobes.Fromtheevidenceofthispreliminarystudy frequently,however,wewillattendmoretoitsinternal JenkinsandBurtonsuggestthataverageimagesshould features, to see direction of gaze, expression and lip be used on identity documents such as passports to movements, which are all important for other social improve both human and computer use of such functions(seeBruceandYoung,1998foranintroduc- images. toryoverview).Moreover,hairstylewillvaryfromone So,ourrepresentationsofunfamiliarfacesmakeit occasion to another, and people may sometimes wear verydifficulttogeneralisetonovelviews,expressions hatsorscarves.Thusitisnotsurprisingthatthevisual and contexts, while our representations of familiar 2
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