Table Of ContentAdvanced Information and Knowledge Processing
SeriesEditors
ProfessorLakhmiJain
[email protected]
ProfessorXindongWu
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Forothertitlespublishedinthisseries,goto
www.springer.com/series/4738
Dorothy Monekosso · Paolo Remagnino
Yoshinori Kuno
Editors
Intelligent Environments
Methods, Algorithms and Applications
(cid:65)(cid:66)(cid:67)
Editors
DorothyMonekosso,PhD PaoloRemagnino,PhD
KingstonUniversity,UK KingstonUniversity,UK
YoshinoriKuno,PhD
SaitamaUniversity,Japan
AI&KPISSN:1610-3947
ISBN:978-1-84800-345-3 e-ISBN:978-1-84800-346-0
DOI:10.1007/978-1-84800-346-0
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Preface
Relatively new research fields such as ambient intelligence, intelligent environ-
ments, ubiquitous computing, and wearable devices have emerged in recent years.
These fields are related by a common theme: making use of novel technologies
to enhance user experience by providing user-centric intelligent environments, re-
movingcomputersfromthedesktopandmakingcomputingavailableanywhereand
anytime.Itmustbesaidthattheconceptofintelligentenvironmentsisnotnewand
beganwithhomeautomation.Thechoiceofnameforthefieldvariessomewhatfrom
continenttocontinentintheEnglish-speakingworld.Ingeneralintelligentspaceis
synonymous to intelligent environments or smart spaces of which smart homes is
a subfield. In this collection, the terms intelligent environments and ambient intel-
ligenceareusedinterchangeablythroughout.Suchenvironmentsaremadepossible
by permeating living spaces with intelligent technology that enhances quality of
life.Inparticular,advancesintechnologiessuchasminiaturizedsensors,advances
in communication and networking technology including high-bandwidth wireless
devicesandthereductioninpowerconsumptionhavemadepossibletheconceptof
intelligentenvironments.Environmentssuchasahome,anoffice,ashoppingmall,
and a travel port utilize data provided by users to adapt the environment to meet
the user’s needs and improve human-machine interactions. The user information
is gathered either via wearable devices or by pervasive sensors or a combination
of both. Intelligent environments brings together a number of research fields from
computerscience,suchasartificialintelligence,computervision,machinelearning,
and robotics as well as engineering and architecture. Other fields such as human-
computerinteractionandsociologydealwiththehumanaspectoftheproblems.
May2008 DorothyMonekosso
LondonandTokyo PaoloRemagnino
YoshinoriKuno
vii
Contents
Preface............................................................ vii
ListofContributors ................................................ xv
1 IntelligentEnvironments:Methods,AlgorithmsandApplications ... 1
DorothyN.Monekosso,PaoloRemagnino,andYoshinoriKuno
1.1 IntelligentEnvironments ................................... 1
1.1.1 WhatIsAnIntelligentEnvironment? ................. 2
1.1.2 HowIsAnIntelligentEnvironmentBuilt?............. 2
1.2 TechnologyforIntelligentEnvironments...................... 2
1.3 ResearchProjects ......................................... 4
1.3.1 PrivateSpaces .................................... 4
1.3.2 PublicSpaces..................................... 5
1.3.3 Middleware ...................................... 7
1.4 ChapterThemesinThisCollection .......................... 8
1.5 Conclusion............................................... 9
References..................................................... 10
2 APervasiveSensorSystemforEvidence-BasedNursing
CareSupport............................................... 13
ToshioHori,YoshifumiNishida,andShin’ichiMurakami
2.1 Introduction.............................................. 13
2.2 Evidence-BasedNursingCareSupport ....................... 14
2.2.1 BackgroundoftheProject .......................... 14
2.2.2 ConceptofEvidence-BasedNursingCareSupport...... 15
2.2.3 InitialGoaloftheProject:FallsPrevention ............ 16
2.2.4 SecondGoaloftheProject:ObtainingADL
ofInhabitants..................................... 17
2.3 RelatedWork............................................. 18
ix
x Contents
2.4 OverviewandImplementationsoftheSystem ................. 19
2.4.1 Overview of the Evidence-Based Nursing Care
SupportSystem ................................... 19
2.4.2 SystemImplementations ........................... 20
2.5 ExperimentsandAnalyses.................................. 24
2.5.1 TrackingaWheelchairforFallsPrevention ............ 24
2.5.2 ActivityTransitionDiagram:TransitionofActivities
inOneDay....................................... 25
2.5.3 QuantitativeEvaluationofDailyActivities ............ 26
2.5.4 Probabilityof“Toilet”Activity ...................... 28
2.5.5 DiscussionoftheExperimentalResults ............... 29
2.6 ProspectoftheEvidence-BasedNursingCareSupportSystem ... 30
2.7 Conclusions.............................................. 31
References..................................................... 32
3 AnomalousBehaviorDetection:SupportingIndependentLiving.... 35
DorothyN.MonekossoandPaoloRemagnino
3.1 Introduction.............................................. 35
3.2 Relatedwork............................................. 36
3.3 Methodology............................................. 37
3.3.1 UnsupervisedClassificationTechniques............... 37
3.3.2 UsingHMMtoModelBehavior ..................... 38
3.4 ExperimentalSetupandDataCollection ...................... 39
3.4.1 NoisyData:SourcesofError........................ 40
3.4.2 Learningactivities................................. 40
3.5 ExperimentalResults ...................................... 41
3.5.1 InstanceClassAnnotation .......................... 41
3.5.2 DataPreprocessing ................................ 41
3.5.3 Models:UnsupervisedClassification:Clustering
andAllocationofActivitiestoClusters ............... 43
3.5.4 Behaviors:DiscoveringPatternsinActivities .......... 45
3.5.5 Behaviors:DiscoveringAnomalous
PatternsofActivity ................................ 46
3.6 Discussion ............................................... 48
3.7 Conclusions.............................................. 49
References..................................................... 49
4 SequentialPatternMiningforCooking-SupportRobot............ 51
YasushiNakauchi
4.1 Introduction.............................................. 51
4.2 SystemDesign ........................................... 53
4.2.1 InferencefromSeriesofHumanActions .............. 53
4.2.2 TimeSequenceDataMining ........................ 54
4.2.3 HumanBehaviorInferenceAlgorithm ................ 54
4.2.4 ActivitySupportofHuman ......................... 57
Contents xi
4.3 Implementation........................................... 59
4.3.1 ICTagSystem .................................... 59
4.3.2 InferenceofHuman’sNextAction ................... 60
4.3.3 CookingSupportInterface .......................... 61
4.4 ExperimentalResults ...................................... 63
4.5 Conclusions.............................................. 65
References..................................................... 66
5 Robotic,SensoryandProblem-SolvingIngredients
fortheFutureHome......................................... 69
Amedeo Cesta, Luca Iocchi, G. Riccardo Leone, Daniele Nardi,
FedericoPecora,andRiccardoRasconi
5.1 Introduction.............................................. 69
5.1.1 ComponentsoftheMultiagentSystem ............... 70
5.2 TheRoboticPlatformMobilitySubsystem .................... 71
5.3 TheInteractionManager ................................... 73
5.4 Environmental Sensors for People Tracking
andPostureRecognition ................................... 74
5.5 MonitoringActivitiesofDailyLiving ........................ 76
5.5.1 ScheduleRepresentationandExecutionMonitoring..... 77
5.5.2 ConstraintManagementintheROBOCAREContext..... 78
5.5.3 FromConstraintViolationstoVerbalInteraction ....... 81
5.6 MultiagentCoordinationInfrastructure ....................... 82
5.6.1 CastingtheMACProblemtoDCOP.................. 83
5.6.2 CooperativelySolvingtheMACProblem ............. 86
5.7 Conclusions.............................................. 87
References..................................................... 88
6 UbiquitousStereoVisionforHumanSensing .................... 91
IkushiYodaandKatsuhikoSakae
6.1 Introduction.............................................. 91
6.2 UbiquitousStereoVision................................... 93
6.2.1 ConceptofUbiquitousStereoVision ................. 93
6.2.2 Server-ClientModelforUSV ....................... 93
6.2.3 RealUtilizationCases.............................. 94
6.3 HierarchicalUtilizationof3DDataandPersonalRecognition .... 95
6.3.1 Acquisitionof3DRangeInformation................. 95
6.3.2 ProjectiontoFloorPlane ........................... 96
6.4 RecognitionofMultiplePersonsandInterface ................. 98
6.4.1 PoseRecognitionforMultiplePeople................. 99
6.4.2 PersonalIdentification .............................100
6.4.3 InterfaceforSpaceControl .........................101
6.5 Human Monitoring in Open Space (Safety
ManagementApplication) ..................................101
6.5.1 MonitoringRailroadCrossing .......................101
6.5.2 StationPlatformEdgeSafetyManagement ............103
xii Contents
6.5.3 MonitoringHugeSpace ............................104
6.6 ConclusionandFutureWork................................105
References.....................................................106
7 AugmentingProfessionalTraining,anAmbient
IntelligenceApproach........................................ 109
B.Zhan,D.N.Monekosso,S.Rush,P.Remagnino,andS.A.Velastin
7.1 Introduction..............................................109
7.2 ColorTrackingofPeople...................................112
7.3 CountingPeoplebySpatialRelationshipAnalysis..............113
7.3.1 SimplePeopleCountingAlgorithm ..................113
7.3.2 GraphsofBlobs...................................114
7.3.3 EstimationofDistanceBetweenBlobs................116
7.3.4 TemporalPyramidforDistanceEstimation ............117
7.3.5 ProbabilisticEstimationofGroupings ................119
7.3.6 GroupingBlobs ...................................120
7.4 ExperimentalResults ......................................121
7.5 Conclusions..............................................124
References.....................................................124
8 StereoOmnidirectionalSystem(SOS)andItsApplications......... 127
YutakaSatohandKatsuhikoSakaue
8.1 Introduction..............................................127
8.2 SystemConfiguration......................................128
8.3 Imageintegration .........................................131
8.4 GenerationofStableImagesatArbitraryRotation..............133
8.5 AnexampleApplication:IntelligentElectricWheelchair ........136
8.5.1 Overview ........................................136
8.5.2 SystemConfiguration ..............................136
8.5.3 ObstacleDetection ................................138
8.5.4 Gesture/PostureDetection .........................140
8.6 Conclusions..............................................140
References.....................................................140
9 VideoAnalysisforAmbientIntelligenceinUrbanEnvironments.... 143
AndreaPratiandRitaCucchiara
9.1 Introduction..............................................143
9.2 VisualDataforUrbanAmI .................................144
9.2.1 VideoSurveillanceinUrbanEnvironment.............145
9.2.2 TheLAICAProject................................148
9.3 AutomaticVideoProcessingforPeopleTracking ..............149
9.3.1 PeopleDetectionandTrackingfromSingle
StaticCamera.....................................150
9.3.2 PeopleDetectionandTracking
fromDistributedCameras ..........................152
Contents xiii
9.3.3 PeopleDetectionandTracking
fromMovingCameras .............................154
9.4 PrivacyandEthicalIssues ..................................155
References.....................................................157
10 FromMonomodaltoMultimodal:AffectRecognition
UsingVisualModalities ...................................... 161
HaticeGunesandMassimoPiccardi
10.1 Introduction..............................................161
10.2 OrganizationoftheChapter.................................163
10.3 FromMonomodaltoMultimodal:ChangesandChallenges ......164
10.3.1 BackgroundResearch..............................164
10.3.2 DataCollection ...................................168
10.3.3 DataAnnotation ..................................169
10.3.4 Synchrony/AsynchronyBetweenModalities ...........171
10.3.5 DataIntegration/Fusion ............................172
10.3.6 InformationComplementarity/Redundancy............174
10.3.7 InformationContentofModalities ...................176
10.4 Monomodal Systems Recognizing Affective Face
orBodyMovement........................................177
10.5 Multimodal Systems Recognizing Affect from Face
andBodyMovement ......................................179
10.5.1 Project1:MultimodalAffectAnalysisforFutureCars ..179
10.5.2 Project 2: Emotion Analysis in Man-Machine
InteractionSystems................................182
10.5.3 Project3:MultimodalAffectRecognitioninLearning
Environments.....................................183
10.5.4 Project 4: FABO-Fusing Face and Body Gestures
forBimodalEmotionRecognition ...................184
10.6 MultimodalAffectSystems:TheFuture ......................185
References.....................................................187
11 ImportanceofVisioninHuman-RobotCommunication:
UnderstandingSpeechUsingRobotVisionandDemonstrating
ProperActionstoHumanVision............................... 191
YoshinoriKuno,MichieKawashima,KeiichiYamazaki,
andAkikoYamazaki
11.1 Introduction..............................................191
11.2 UnderstandingSimplifiedUtterancesUsingRobotVision .......193
11.2.1 InexplicitUtterances...............................193
11.2.2 InformationObtainedbyVision .....................194
11.2.3 LanguageProcessing ..............................195
11.2.4 VisionProcessing .................................195
11.2.5 SynchronizationBetweenSpeechandVision ..........197
11.2.6 Experiments......................................199
