Digitally Archiving Cultural Objects

506 Pages·2007·31.47 MB·English

by  Katsushi Ikeuchi

DIGITALLY ARCHIVING
CULTURAL OBJECTS
DIGITALLY ARCHIVING
CULTURAL OBJECTS

Katsushi Ikeuchi
The University of Tokyo

Daisuke Miyazaki
The University of Tokyo
Katsushi Ikeuchi Daisuke Miyazaki
The University of Tokyo The University of Tokyo
Institute of Industrial Science Institute of Industrial Science
4-6-1 Komaba, Meguro-ku 4-6-1 Komaba, Meguro-ku
Tokyo, Japan Tokyo, Japan
[email protected] [email protected]

Library of Congress Control Number: 2007936975

Digitally Archiving Cultural Objects
by Katsushi Ikeuchi and Daisuke Miyazaki

ISBN-13: 978-0-387-75806-0 e-ISBN-13: 978-0-387-75807-7

Printed on acid-free paper.

© 2008 Springer Science+Business Media, LLC
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Preface
In1898,theEnglishwriterH.G.Wellsintroducedtheideaoftimetravelin
hisnovel, TheTime Machine. Here at the IkeuchiLaboratory, theUniversity
ofTokyo,wehaveassembledagroupofworld-classengineerswhoseworkin
computervisionletsustravelbackintimetothe7thcenturytotherootsofour
Japanese culture and to preserve cultural objects through the magic of three-
dimensionaldigitalconversion. TheGreatBuddhaofNarawasoriginallybuilt
inthe seventhcenturyby order of theemperor, butit wasburneddowntwice
during civil wars in Japan. The current Buddha was rebuilt in the sixteenth
century. Usingadvancedcomputervision, computergraphicstechniques,and
historic knowledgefrom documentspreserved in theTodaijitemple, we have
reconstructedtheBuddhaandBuddhapalace.
Another example of digital restoration is the work we have done with the
Bayon Temple in Angkor Thom, Cambodia. This temple, which unites the
Buddhist outlook of ancientIndia withKhmer tradition, isone of themaster-
piecesofhistoricarchitecture. Unfortunately,thestructureisworseningdayby
day,andthereisahighpossibilityofitscollapsinginthenearfuture. Byusing
newlydevelopedsensorsandsoftware,wehavedigitizedthishugetempleand
obtained3Ddigitaldataforrestorationpurposes.
Whyaretheserestorationprojectsnecessary? Unfortunately,manyvaluable
objectsthatformpartofourculturalheritagehavebeendecayedbyweathering
andnaturaldisasterssuchasIndonesia’srecentearthquake. Otherobjectshave
been destroyedthrough man-made disasterssuch as the Taliban’s destruction
of the great Barmian Buddha in Afghanistan. But we can preserve our irre-
placeable culturalheritage in 3D digital form for future generationsusingto-
day’sITtechnologies. Imagesderivedfrom3Ddigitaltechnologydeepenour
understandingsofourculturalheritageandincreasetheidentityanddignityof
eachnation.
Thisbookpresentsanoverviewoftheresultsofresearchoninformationand
communication technologies devoted to digital preservation. It summarizes
recentresearchresultsaccumulatedsincethepublicationofourpreviousbook,
vi DIGITALLYARCHIVINGCULTURALOBJECTS
ModelingFromReality. Ournewbookconsistsoffourparts. PartIintroduces
our cutting-edge range sensors for scanning cultural objects. Part II presents
our software algorithm, which integrates a large amount of range data into a
unified mesh model. Part III explains techniques to analyze the color of the
surfaces of cultural objects for preserving their “true surface color.” Part IV
providesexamples ofhowtoutilize thesedigital dataforthe“time-machine.”
Wehopeourreadersenjoytheirjourneytothisrestoredworld.
Research results presented in this book are supported by three major re-
search projects. We are deeply indebted to three leading program managers
oftheprojects: ProfessorMasaoSakauchiofNationalInstituteofInformatics
fortheSinProgram,ProfessorMakotoNagaoofNationalLibraryofJapanese
Diets for the CREST program, and Professor Hiroshi Harashima of the Uni-
versity of Tokyo for the LP program for their guidance, management as well
as financial supports. We extend our sincere appreciationtoDr. JoanKnapp,
who revised our text; we could not have produced this book without her de-
voted help. We also thank our secretaries, Ms. Keiko Motoki, Ms. Yoshiko
Matsuura,andMs.KaoruKikuchiforputtingourmaterialinorder. Thecover
of this book was designed by Tetsuya Kakuta. This research was financially
supported inpart bythe Ministryof Education, Culture, Sports, Science, and
TechnologyoftheJapanesegovernment,andinpartbytheJapanScienceand
TechnologyAgency.
Katsushi Ikeuchi
Daisuke Miyazaki
DIGITALLYARCHIVINGCULTURALOBJECTS vii
(cid:2)c2005IEEE.Reprinted,withpermission,fromAtsuhikoBannoandKatsushiIkeuchi,“ShapeRecoveryof
3DDataObtainedfromaMovingRangeSensor,”ProceedingsofIEEEInternationalConferenceonComputer
Vision,pp.792-799,2005.
(cid:2)c2005IEEE.Reprinted,withpermission,fromKenMatsui,ShintaroOno,andKatsushiIkeuchi,“TheClimb-
ingSensor:3-DModelingofaNarrowandVerticallyStalkySpacebyUsingSpatio-TemporalRangeImage,”
ProceedingsofIEEE/RSJInternationalConferenceonIntelligentRobotsandSystems,pp.3997-4002,2005.
(cid:2)c2005IEEE.Reprinted,withpermission,fromDaisukeMiyazakiandKatsushiIkeuchi,“InversePolarization
Raytracing:EstimatingSurfaceShapesofTransparentObjects,”ProceedingsofIEEEComputerSocietyInter-
nationalConferenceonComputerVisionandPatternRecognition,pp.910-917,2005.
(cid:2)c2005IEEE.Reprinted,withpermission,fromTakeshiOishi,AtsushiNakazawa,RyoKurazume,andKat-
sushiIkeuchi,“FastSimultaneousAlignmentofMultipleRangeImagesusingIndexImages,”Proceedingsof
InternationalConferenceon3-DDigitalImagingandModeling,pp.476-483,2005.
(cid:2)c2003IEEE.Reprinted,withpermission,fromTakeshiOishi,RyusukeSagawa,AtsushiNakazawa,RyoKu-
razume,andKatsushiIkeuchi,“ParallelAlignmentofLargeNumberofRangeImages,”ProceedingsofInterna-
tionalConferenceon3-DDigitalImagingandModeling,pp.195-202,2003.
(cid:2)c2005IEEE.Reprinted,withpermission,fromTomohitoMasuda,YuichiroHirota,KoNishino,andKatsushi
Ikeuchi,“SimultaneousDeterminationofRegistrationandDeformationParametersamong3DRangeImages,”
ProceedingsofInternationalConferenceon3-DDigitalImagingandModeling,pp.369-376,2005.
(cid:2)c2001IEEE.Reprinted,withpermission,fromRyusukeSagawa,KoNishino,MarkD.Wheeler,andKatsushi
Ikeuchi,“ParallelProcessingofRangeDataMerging,”ProceedingsofIEEE/RSJInternationalConferenceon
IntelligentRobotsandSystems,pp.577-583,2001.
(cid:2)c2005IEEE.Reprinted,withpermission,fromRyusukeSagawa,KoNishino,andKatsushiIkeuchi,“Adap-
tivelyMergingLarge-ScaleRangeDatawithReflectanceProperties,”IEEETransactionsonPatternAnalysis
andMachineIntelligence,vol.27,no.3,pp.392-405,2005.
(cid:2)c2002IEEE.Reprinted,withpermission,fromRyusukeSagawa,TakeshiOishi,AtsushiNakazawa,RyoKu-
razume,andKatsushiIkeuchi,“IterativeRefinementofRangeImageswithAnisortropicErrorDistribution,”
ProceedingsofIEEE/RSJInternationalConferenceonIntelligentRobotsandSystems,pp.79-85,2002.
(cid:2)c2003IEEE.Reprinted,withpermission,fromRyusukeSagawaandKatsushiIkeuchi,“TakingConsensusof
SignedDistanceFieldforComplementingUnobservableSurface,”ProceedingsofInternationalConferenceon
3-DDigitalImagingandModeling,pp.410-417,2003.
(cid:2)c2005IEEE.Reprinted,withpermission,fromReiKawakami,RobbyT.Tan,andKatsushiIkeuchi,“Consistent
SurfaceColorforTexturingLargeObjectsinOutdoorScenes,”ProceedingsofIEEEInternationalConference
onComputerVision,pp.1200-1207,2005.
(cid:2)c2005IEEE.Reprinted,withpermission,fromRobbyT.TanandKatsushiIkeuchi,“SeparatingReflection
ComponentsofTexturedSurfacesUsingaSingleImage,”IEEETransactionsonPatternAnalysisandMachine
Intelligence,vol.27,no.2,pp.179-193,2005.
(cid:2)c2005IEEE.Reprinted,withpermission,fromTetsuyaKakuta,TakeshiOishi,andKatsushiIkeuchi,“Shading
andShadowingofArchitectureinMixedReality,”ProceedingsofIEEEandACMInternationalSymposiumon
MixedandAugmentedReality,pp.200-201,2005.
(cid:2)c2003IEEE.Reprinted,withpermission,fromKatsushiIkeuchi,AtsushiNakazawa,KazuhideHasegawa,and
TakeshiOhishi,“TheGreatBuddhaProject:ModelingCulturalHeritageforVRSystemsthroughObservation,”
ProceedingsofIEEEandACMInternationalSymposiumonMixedandAugmentedReality,pp.7-16,2003.
Contents
Preface v
ListofFigures xvii
ListofTables xxxiii
1
Introduction 1
KatsushiIkeuchiandDaisukeMiyazaki
1. RangeSensor 2
2. RangeDataAnalysis 3
3. PhotometricModelling 6
4. UtilizingDigitalDataforArchaeologicalInvestigation 7
Acknowledgments 9
References 9
PartI RangeSensor
2
ShapeRectificationof3DDataObtainedbyaMovingRangeSensorby 13
usingImageSequences
AtsuhikoBannoandKatsushiIkeuchi
1. Introduction 13
2. FullPerspectiveFactorization 15
3. Refinement 19
4. FLRS 21
5. Experiments 23
6. Conclusions 26
Acknowledgments 26
References 26
3
The Climbing Sensor: 3D Modeling of Narrow Areas byUsing Space- 33
TimeAnalysis
ShintaroOno,KenMatsui,andKatsushiIkeuchi
1. Introduction 33
2. SpatiotemporalRangeImage 35
3. LocalizingAlgorithmfor3DModeling 38
4. SystemConfiguration 39
x DIGITALLYARCHIVINGCULTURALOBJECTS
5. ExperimentandModelingResults 41
6. Conclusion 44
Acknowledgments 45
References 46
4
InversePolarizationRaytracing:EstimatingSurfaceShapesofTranspar- 49
entObjects
DaisukeMiyazakiandKatsushiIkeuchi
1. Introduction 49
2. PolarizationRaytracing 51
3. InversePolarizationRaytracing 56
4. MeasurementResult 58
5. Conclusion 63
Acknowledgments 64
References 64
PartII RangeDataAnalysis
5
RobustSimultaneousRegistrationofMultipleRangeImages 71
KoNishinoandKatsushiIkeuchi
1. Introduction 71
2. Overview 72
3. PointMateSearch 75
4. Least-squareMinimizationStrategy 79
5. Results 82
6. ConclusionandFutureWork 84
Acknowledgments 85
References 86
6
AFastSimultaneousAlignmentofMultipleRangeImages 89
TakeshiOishi,AtsushiNakazawa,RyoKurazume,andKatsushiIkeuchi
1. Introduction 89
2. AlignmentAlgorithm 91
3. ExperimentalResults 99
4. Conclusion 104
Acknowledgments 106
References 106
7
ParallelAlignmentofaLargeNumberofRangeImages 109
Takeshi Oishi, Ryusuke Sagawa, Atsushi Nakazawa, Ryo Kurazume, and Katsushi
Ikeuchi
1. Introduction 109
2. SimultaneousAlignmentAlgorithm 110
3. ParallelAlignmentBasedonaPCCluster 112
Contents xi
4. PerformanceEvaluation 118
5. ExperimentalResults 121
6. Conclusion 124
Acknowledgments 124
References 124
8
Simultaneous Determination of Registration and Deformation Parame- 127
tersamong3DRangeImages
TomohitoMasuda,YuichiroHirota,KoNishino,andKatsushiIkeuchi
1. Introduction 127
2. RelatedWork 129
3. RobustDeterminationofTranslationandRotationParameters 130
4. SimultaneousDeterminationofDeformationParameters 132
5. UnknownParameterEstimationofMathematicalModel 134
6. Inter-and-IntraScanningRegistration 138
7. ConclusionandFutureWork 143
Acknowledgments 144
References 144
9
ParallelProcessingofRangeDataMerging 147
RyusukeSagawa,KoNishino,MarkD.Wheeler,andKatsushiIkeuchi
1. Introduction 147
2. DataMerging 148
3. Increasethecomputationandmemoryefficiency 152
4. ParallelComputingofSignedDistances 153
5. PerformanceEvaluation 155
6. Conclusion 157
Acknowledgments 157
References 158
10
AdaptivelyMergingLarge-ScaleRangeDatawithReflectanceProperties 161
RyusukeSagawa,KoNishino,andKatsushiIkeuchi
1. Introduction 161
2. ConsensusSurfaceAlgorithm 166
3. AdaptiveMergingAlgorithm 168
4. AdaptiveMergingwithReflectanceProperties 173
5. AdaptiveNearestNeighborSearch 177
6. Experiments 179
7. Conclusion 183
Appendix:AlgorithmofBOTtest 186
Acknowledgments 187
References 187
11
IterativeRefinementofRangeImageswithAnisotropicErrorDistribution 193