Brain, Body and Machine: Proceedings of an International Symposium on the Occasion of the 25th Anniversary of the McGill University Centre for Intelligent Machines

361 Pages·2010·11.92 MB·English

by  Bruno Siciliano

Jorge Angeles, Benoit Boulet, James J. Clark,
József Kövecses, and Kaleem Siddiqi (Eds.)
Brain, Body and Machine
Proceedings of an International Symposium
on the Occasion of the 25th Anniversary
of the McGill University Centre
for Intelligent Machines
ABC
Editors
Prof.JorgeAngeles Prof.JózsefKövecses
DepartmentofMechanicalEngineering& DepartmentofMechanicalEngineering&
CentreforIntelligentMachines CentreforIntelligentMachines
McGillUniversity McGillUniversity
817SherbrookeSt.W. 817SherbrookeSt.West
Montreal,Quebec Montreal,Quebec
CanadaH3A2K6 CanadaH3A2K6
E-mail:[email protected] E-mail:[email protected]
Prof.BenoitBoulet
Prof.KaleemSiddiqi
DepartmentofElectricaland
SchoolofComputerScience&
ComputerEngineering&
CentreforIntelligentMachines
CentreforIntelligentMachines
McGillUniversity
McGillUniversity
3480UniversityStreet
3480UniversityStreet
Montreal,QC
Montreal,Quebec
CanadaH3A2A7
CanadaH3A2A7
E-mail:[email protected]
E-mail:[email protected]
Prof.JamesClark
DepartmentofElectricaland
ComputerEngineering&
CentreforIntelligentMachines
McGillUniversity
3480UniversityStreet
Montreal,Quebec
CanadaH3A2A7
E-mail:[email protected]
ISBN978-3-642-16258-9 e-ISBN978-3-642-16259-6
DOI10.1007/978-3-642-16259-6
AdvancesinIntelligentandSoftComputing ISSN1867-5662
LibraryofCongressControlNumber:2010937343
(cid:2)c 2010Springer-VerlagBerlinHeidelberg
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Preface
The Centre for IntelligentMachines(CIM), McGill University,was officially cre-
atedonNovember13th,1985,uponapprovalbytheUniversitySenate.Themission
of the centre is, since its inception, “to excel in the field of intelligent systems,
stressing basic research, technology development and education.” Intelligent ma-
chinesareunderstood,alongtheselines,assystems“capableofadaptingtheirgoal-
orientedbehaviorbysensingandinterpretingtheirenvironment,makingdecisions
andplans,andthen carryingoutthoseplansusingphysicalactions.”Researchac-
tivitiesofinteresttoCIMincluderobotdesign,mechanicalsystemdynamics,robot
control,computervision,visualperception,medicalimaging,haptics,systemtheory
andapplications,andvirtualenvironments.Thesefieldscanbesuccinctlydescribed
bythetitleoftheinternationalsymposiumrecordedinthisbook,Brain,Bodyand
Machine(BBM).
CIM’sobjectofresearchisthusreflectedinthebook,wherereaderswillfindthat
mostpaperscoveratleasttwoofthethreemainthrusts.Papersreflectthestate-of-
the-artofthemultidisciplineofintelligentmachines,nowadayshighlydiversified.A
broadspectrumofapplicationsiscovered,fromhumanoidrobotsandautonomous
planetaryrovers,toinnovativeproceduresandsystemsforshape-reproductionand
onto systemsor devicesformedicaldiagnosis.Applicationsareallgearedto one
commongoal,abetterqualityoflifeforhighlychallengedpatientsorsimplyforthe
healthy individual. Methods to face the challenges include not only sophisticated
deterministicalgorithms,butalsotheirheuristiccounterparts,attherootsofwhatis
knownassoftcomputing.
The readerwill find here paperson human-robotinteraction as well as human-
safety algorithms;haptic interfaces;innovativeinstrumentsand algorithmsfor the
sensing of motion and the identification of brain neoplasms; even a paper on a
saxophone-playingrobot.
VI Preface
In its first 25 years, CIM has produced hundreds of graduates at the Master’s,
Ph.D. andpostdoctorallevels. These alumnaeandalumniare now successfulpro-
fessors,researchers,developersandmanagerswhoareattheforefrontofmanyin-
dustries,andentrepreneursandbusinessdevelopers.CIM’sgraduates,moreover,are
distributedallovertheworld.ThisrichdistributionmadetheInternationalSympo-
siumonBrain,BodyandMachinepossible.
Montreal, TheEditors
August2010 JorgeAngeles
BenoitBoulet
JamesJ.Clark
Jo´zsefKo¨vecses
KaleemSiddiqi
Acknowledgements
McGill University’sCentre for IntelligentMachines (CIM) is the productof a vi-
sionary,ProfessorPierreBelanger,whostartedpromotingtheideaasChairmanof
ElectricalEngineeringintheearlyeighthies.Hegatheredagroupofcolleaguesin
hisdepartment,in the Schoolof ComputerScience andin the DepartmentofMe-
chanicalEngineering,inaneffortthatculminatedwiththecreationof“thecentre”
on November 13, 1985. Since 2007, CIM has been stregthened by the financial
and strategic support provided by Quebec’s Fonds de recherche sur la nature et
les technologiesvia a grantto the Regroupementstrate´gique pour l’e´tude des en-
vironnementspartage´sintelligents re´partis (RE´PARTI), a network of five Quebec
universitiessharingthesame researchinterestsasMcGillin thedomainofintelli-
gentsystems.Infact,RE´PARTIhasenhancedCIM’snetworkingactivitiesbeyond
QuebecandCanada.
Forthesuccessfulcelebrationofthefirst25yearsofCIM,weareindebtedtothe
DeansofEngineering,Prof.ChristophePierre,andofScience,Prof.MartinGrant,
totheChairmenofElectricalandComputerEngineering,Prof.DavidPlant,andof
MechanicalEngineering,GeorgeHaller,aswellastotheDirectoroftheSchoolof
ComputerScience,Prof.GregoryDudek,whosupportedandencouragedoureffort.
ThelogisticsupportprovidedbyJanBinder,SystemsManager,notonlyduringthe
celebration,butalsoduringmostofthepast25years,hasplayedadecisiverolein
makingofCIMasuccessstory.MarleneGray,Manager,CynthiaDavidson,Secre-
tary,andPatrickMcLean,SystemsAdministrator,haveprovidedexcellentsupport
in keepingthe centrerunningthroughoutthe years,andcertainlyduringthiscele-
bratory year. The celebration activities have run through the year, with six public
seminars and one Beatty Lecture, given by prominent researchers in the areas of
brain,bodyandmachine.
Last,butnotleast,theEditorswanttoacknowledgethosewhoparticipatedinthe
productionofthisbook:allCIMmembers,whocomposedtheTechnicalCommit-
tee of the InternationalSymposium on Brain, Body and Machine; the anonymous
reviewerswho providednot only their expertise, but also their precioustime; and
the key role playedby Dr. SeyedhosseinHajzargarbashi,the managerof the sym-
posiumwebsite.Alltheseindividualscontributedtosecuringahighqualityofour
finalproduct:thisbook.
Contents
ForceandVisualControlforSafeHuman-RobotInteraction........... 1
BrunoSiciliano,LuigiVillani,VincenzoLippiello,AgostinoDeSantis
1 Introduction .............................................. 1
2 Modeling ................................................ 2
2.1 HumanUser ....................................... 3
2.2 Environment ....................................... 4
2.3 Robot............................................. 5
2.4 Camera ........................................... 5
3 UseofVision,ForceandJointPositionsMeasurements.......... 6
3.1 Vision............................................. 6
3.2 Force ............................................. 7
3.3 JointPositions...................................... 7
4 Vision-BasedPoseEstimation............................... 8
4.1 HumanOperator’sPoseEstimation .................... 8
4.2 ObjectPoseEstimation .............................. 8
5 InteractionControl ........................................ 9
5.1 HybridForce/PositionControl ........................ 10
5.2 ImpedanceControl.................................. 11
6 CaseStudies.............................................. 12
6.1 InteractionwithanObject............................ 13
6.2 Vision-BasedHeadAvoidance ........................ 14
7 Conclusions .............................................. 15
References.................................................... 16
3DAutomaticSegmentationoftheHippocampusUsing
WaveletswithApplicationstoRadiotherapyPlanning ................. 17
YiGao,BenjaminW.Corn,DanSchifter,AllenTannenbaum
1 Introduction .............................................. 18
2 MethodandMaterials ..................................... 20
2.1 ShapeLearning .................................... 21
2.2 ShapeBasedSegmentation .......................... 23
X Contents
2.3 ShapeInitialization ................................. 24
2.4 DataDrivenSegmentation............................ 24
2.5 ShapeFilteringwithShapePrior ...................... 25
2.6 SeparationoftheHippocampusandAmygdala .......... 26
3 Results .................................................. 26
3.1 HippocampusandAmygdalaSegmentationResults ...... 27
3.2 SegmentationResultsShownbySlices ................. 27
3.3 DistanceonMesh................................... 28
3.4 FurtherQuantitativeAnalysis ......................... 29
4 Discussion ............................................... 30
References.................................................... 30
RigidRegistrationof3DUltrasoundandMRI:Comparing
TwoApproachesonNineTumorCases............................... 33
LaurenceMercier,VladimirFonov,RolandoF.DelMaestro,
KevinPetrecca,LasseR.Østergaard,D.LouisCollins
1 Introduction .............................................. 33
2 MaterialsandMethods ..................................... 35
2.1 ClinicalData....................................... 35
2.2 Pseudo-ultrasoundGeneration ........................ 35
2.3 NormalizedMutualInformationTechnique ............. 37
2.4 RigidBodyRegistration ............................. 37
2.5 RegistrationValidation .............................. 38
3 Results .................................................. 38
4 Discussion ............................................... 40
5 Conclusions .............................................. 41
References.................................................... 41
ANewApproachtoVirtualMirroringforView
Integration ....................................................... 45
CarmenE.Au,JamesJ.Clark
1 Introduction .............................................. 45
1.1 VirtualMirroringTechnique .......................... 47
2 NewVMApproach........................................ 50
2.1 MakingaTrueVirtualMirror ......................... 50
2.2 AlgorithmforGeneralizedTechnique .................. 52
3 ResultingCompositeImagesforNewVMApproach............ 53
4 LimitationsandFutureWorks ............................... 54
References.................................................... 54
DesigningaMetricfortheDifferencebetweenGaussianDensities ...... 57
KarimT.Abou–Moustafa,FernandoDeLaTorre,FrankP.Ferrie
1 Introduction .............................................. 57
2 RelatedWork............................................. 59
3 DivergencesandDistancesforProbabilityDistributions ......... 60
Contents XI
3.1 DistancesandDivergencesforGaussianDensities........ 61
3.2 ACloseLookatd andd .......................... 62
KL B
4 DesigningaMetricforGaussianDensities .................... 62
4.1 AMetricforSymmetricandPositiveSemi–definite
Matrices........................................... 63
4.2 TheProposedMetricdG ............................. 63
4.3 AKernelBasedondG ............................... 64
5 ExperimentalResults ...................................... 65
5.1 SupervisedDiscriminativeDimensionalityReduction..... 66
5.2 UnsupervisedClusteringofImages .................... 67
References.................................................... 69
PhysicalAsymmetriesandBrightnessPerception ..................... 71
JamesJ.Clark
1 Introduction-IsItDarkorBright? ........................... 71
2 PhysicalAsymmetriesUnderlyingBrightnessPerception ........ 72
2.1 BreakdownoftheLight-DarkRangeAsymmetryDue
toSaturation ....................................... 73
2.2 OtherAsymmetries ................................. 74
3 StatisticalMeasuresofSceneBrightness ...................... 75
4 SurroundEntropyinNaturalImages.......................... 78
5 Summary ................................................ 81
References.................................................... 81
ALearning-BasedPatientRepositioningMethodfrom
Limited-AngleProjections.......................................... 83
Chen-RuiChou,C.BrandonFrederick,ShaX.Chang,
StephenM.Pizer
1 Introduction .............................................. 84
2 ImagingGeometries ....................................... 85
2.1 NanotubeStationaryTomosynthesis(NST) ............. 86
2.2 Limited-AngleCone-BeamCT(CBCT) ................ 86
3 Method.................................................. 86
3.1 TheTrainingStage.................................. 86
3.2 TheTreatmentStage ................................ 87
3.3 HierarchicalTrainings ............................... 88
4 Results .................................................. 89
4.1 TestEnvironments .................................. 89
4.2 TestsonOblique-AngleNSTandLimited-AngleCBCT... 90
5 DiscussionandConclusion ................................. 93
References.................................................... 94
XII Contents
ImageandVideoRegionSaliencyBasedonSpaceandMotion.......... 95
JianLi,MartinLevine,XiangjingAn,ZhenpingSun,HangenHe
1 Introduction .............................................. 95
2 TheMethodology ......................................... 97
2.1 SuppressingRepeatingPatternsforSaliency
Pop-Out........................................... 97
2.2 TheSaliencyMap................................... 101
2.3 ComputingtheVideoSaliencyMap ................... 103
3 Experiments.............................................. 104
3.1 SaliencyDetectionin1-DSignalsand2-DPatterns....... 104
3.2 SaliencyDetectioninNaturalImages .................. 105
3.3 ComputingVideoSaliencyMaps ..................... 106
4 Discussion ............................................... 108
References.................................................... 109
GeneralizedPCAviatheBackwardStepwiseApproachin
ImageAnalysis.................................................... 111
SungkyuJung,XiaoxiaoLiu,J.S.Marron,StephenM.Pizer
1 Introduction .............................................. 111
2 ForwardandBackwardStepwiseViewofPCA................. 113
2.1 MathematicalDevelopmentforEuclideanPCA .......... 113
2.2 PCAApproachesforManifoldData ................... 115
3 Method.................................................. 116
3.1 PrincipalNestedSpheres............................. 117
3.2 ApplicationofPNStoScaledPointDistribution
Models............................................ 119
3.3 ExperimentalResults................................ 120
4 Conclusion............................................... 122
References.................................................... 123
PerformanceofMRF-BasedStereoAlgorithmsforClutteredScenes .... 125
FahimMannan,MichaelLanger
1 Introduction .............................................. 125
2 PreviousWork ............................................ 127
3 ClutteredSceneModelling.................................. 128
4 SyntheticStereoPairGeneration............................. 129
5 Experiments.............................................. 130
5.1 ChoosingSceneParameters .......................... 131
5.2 PerformanceEvaluation.............................. 132
6 Conclusion............................................... 135
References.................................................... 135
Contents XIII
MedialSpheresforShapeApproximation............................ 137
SvetlanaStolpner,PaulKry,KaleemSiddiqi
1 Introduction .............................................. 137
2 BackgroundandPreviousWork ............................. 139
3 ComputationofSpheres.................................... 140
4 VolumetricErrorforUnionsofSpheres ....................... 141
4.1 VolumetricError:ExactorLowerBound ............... 142
4.2 UnionsofSpheres:Tools............................. 142
4.3 ExperimentalResults................................ 143
5 ApproximateSeparationDistance............................ 144
5.1 ImprovingBoundaryCoveragebyConservative
Dilation ........................................... 144
5.2 HierarchyConstructionUsingRectangle-Swept
Spheres ........................................... 145
5.3 ExperimentalResults................................ 146
6 Conclusions .............................................. 147
References.................................................... 148
AHeuristicAlgorithmforSlicingintheRapidFreeze
PrototypingofSculpturedBodies ................................... 149
EricBarnett,JorgeAngeles,DamianoPasini,PieterSijpkes
1 Introduction .............................................. 149
2 DataImportandTransformation ............................. 152
2.1 FacetDataImportationwithfacetread .............. 152
2.2 TransformationofFacetData ......................... 154
3 PartBoundaryPaths ....................................... 154
4 ScaffoldingBoundaryPaths................................. 155
5 PathBuffering ............................................ 156
5.1 TheMatlabbuffermFunction....................... 156
5.2 bufferf,aContourBufferingFunctionforPlanar
Regions ........................................... 157
6 FillPaths ................................................ 159
7 Results .................................................. 160
8 Conclusions .............................................. 160
References.................................................... 161
RobustDesignof2nd OrderTerminalILCUsingμ-Analysis
andaGeneticAlgorithmApproach.................................. 163
GuyGauthier,MathieuBeauchemin-Turcotte,BenoitBoulet
1 Introduction .............................................. 163
2 ProblemSetup ............................................ 164
3 SecondOrderTILCAlgorithm .............................. 165
4 Themu-AnalysisApproach ................................. 167
5 GeneticAlgorithm......................................... 170