Intelligent Environments

by Monekosso, Dorothy; Remagnino, Paolo; Kuno, Yoshinori

• ISBN13: 9781848003453
• ISBN10: 1848003455
• Format: Hardcover
• Copyright: 2008-11-18
• Publisher: Springer-Verlag New York Inc

Summary

"Researchers involved in the Intelligent Environment field are working towards a future where humans live in autonomous and adaptive environments; where public and private spaces are endowed with intelligence that enhances user experience and improves quality of life." "Each chapter in the book describes an example of intelligent environment, focussing on the artificial intelligence technique employed to create the environment. The book also introduces engineering solutions to the problem of understanding and modelling complex scenes via multi-modal arrays of sensors. This collection contains contributions from key researchers in the field."--BOOK JACKET.

Table of Contents

Preface	p. vii
List of Contributors	p. xv
Intelligent Environments: Methods, Algorithms and Applications	p. 1
Intelligent Environments	p. 1
What Is An Intelligent Environment?	p. 2
How Is An Intelligent Environment Built?	p. 2
Technology for Intelligent Environments	p. 2
Research Projects	p. 4
Private Spaces	p. 4
Public Spaces	p. 5
Middleware	p. 7
Chapter Themes in This Collection	p. 8
Conclusion	p. 9
References	p. 10
A Pervasive Sensor System for Evidence-Based Nursing Care Support	p. 13
Introduction	p. 13
Evidence-Based Nursing Care Support	p. 14
Background of the Project	p. 14
Concept of Evidence-Based Nursing Care Support	p. 15
Initial Goal of the Project: Falls Prevention	p. 16
Second Goal of the Project: Obtaining ADL of Inhabitants	p. 17
Related Work	p. 18
Overview and Implementations of the System	p. 19
Overview of the Evidence-Based Nursing Care Support System	p. 19
System Implementations	p. 20
Experiments and Analyses	p. 24
Tracking a Wheelchair for Falls Prevention	p. 24
Activity Transition Diagram: Transition of Activities in One Day	p. 25
Quantitative Evaluation of Daily Activities	p. 26
Probability of "Toilet" Activity	p. 28
Discussion of the Experimental Results	p. 29
Prospect of the Evidence-Based Nursing Care Support System	p. 30
Conclusions	p. 31
References	p. 32
Anomalous Behavior Detection: Supporting Independent Living	p. 35
Introduction	p. 35
Related work	p. 36
Methodology	p. 37
Unsupervised Classification Techniques	p. 37
Using HMM to Model Behavior	p. 38
Experimental Setup and Data Collection	p. 39
Noisy Data: Sources of Error	p. 40
Learning activities	p. 40
Experimental Results	p. 41
Instance Class Annotation	p. 41
Data Preprocessing	p. 41
Models: Unsupervised Classification: Clustering and Allocation of Activities to Clusters	p. 43
Behaviors: Discovering Patterns in Activities	p. 45
Behaviors: Discovering Anomalous Patterns of Activity	p. 46
Discussion	p. 48
Conclusions	p. 49
References	p. 49
Sequential Pattern Mining for Cooking-Support Robot	p. 51
Introduction	p. 51
System Design	p. 53
Inference from Series of Human Actions	p. 53
Time Sequence Data Mining	p. 54
Human Behavior Inference Algorithm	p. 54
Activity Support of Human	p. 57
Implementation	p. 59
IC Tag System	p. 59
Inference of Human's Next Action	p. 60
Cooking Support Interface	p. 61
Experimental Results	p. 63
Conclusions	p. 65
References	p. 66
Robotic, Sensory and Problem-Solving Ingredients for the Future Home	p. 69
Introduction	p. 69
Components of the Multiagent System	p. 70
The Robotic Platform Mobility Subsystem	p. 71
The Interaction Manager	p. 73
Environmental Sensors for People Tracking and Posture Recognition	p. 74
Monitoring Activities of Daily Living	p. 76
Schedule Representation and Execution Monitoring	p. 77
Constraint Management in the RoboCare Context	p. 78
From Constraint Violations to Verbal Interaction	p. 81
Multiagent Coordination Infrastructure	p. 82
Casting the MAC Problem to DCOP	p. 83
Cooperatively Solving the MAC Problem	p. 86
Conclusions	p. 87
References	p. 88
Ubiquitous Stereo Vision for Human Sensing	p. 91
Introduction	p. 91
Ubiquitous Stereo Vision	p. 93
Concept of Ubiquitous Stereo Vision	p. 93
Server-Client Model for USV	p. 93
Real Utilization Cases	p. 94
Hierarchical Utilization of 3D Data and Personal Recognition	p. 95
Acquisition of 3D Range Information	p. 95
Projection to Floor Plane	p. 96
Recognition of Multiple Persons and Interface	p. 98
Pose Recognition for Multiple People	p. 99
Personal Identification	p. 100
Interface for Space Control	p. 101
Human Monitoring in Open Space (Safety Management Application)	p. 101
Monitoring Railroad Crossing	p. 101
Station Platform Edge Safety Management	p. 103
Monitoring Huge Space	p. 104
Conclusion and Future Work	p. 105
References	p. 106
Augmenting Professional Training, an Ambient Intelligence Approach	p. 109
Introduction	p. 109
Color Tracking of People	p. 112
Counting People by Spatial Relationship Analysis	p. 113
Simple People Counting Algorithm	p. 113
Graphs of Blobs	p. 114
Estimation of Distance Between Blobs	p. 116
Temporal Pyramid for Distance Estimation	p. 117
Probabilistic Estimation of Groupings	p. 119
Grouping Blobs	p. 120
Experimental Results	p. 121
Conclusions	p. 124
References	p. 124
Stereo Omnidirectional System (SOS) and Its Applications	p. 127
Introduction	p. 127
System Configuration	p. 128
Image integration	p. 131
Generation of Stable Images at Arbitrary Rotation	p. 133
An example Application: Intelligent Electric Wheelchair	p. 136
Overview	p. 136
System Configuration	p. 136
Obstacle Detection	p. 138
Gesture / Posture Detection	p. 140
Conclusions	p. 140
References	p. 140
Video Analysis for Ambient Intelligence in Urban Environments	p. 143
Introduction	p. 143
Visual Data for Urban AmI	p. 144
Video Surveillance in Urban Environment	p. 145
The LAICA Project	p. 148
Automatic Video Processing for People Tracking	p. 149
People Detection and Tracking from Single Static Camera	p. 150
People Detection and Tracking from Distributed Cameras	p. 152
People Detection and Tracking from Moving Cameras	p. 154
Privacy and Ethical Issues	p. 155
References	p. 157
From Monomodal to Multimodal: Affect Recognition Using Visual Modalities	p. 161
Introduction	p. 161
Organization of the Chapter	p. 163
From Monomodal to Multimodal: Changes and Challenges	p. 164
Background Research	p. 164
Data Collection	p. 168
Data Annotation	p. 169
Synchrony/Asynchrony Between Modalities	p. 171
Data Integration/Fusion	p. 172
Information Complementarity/Redundancy	p. 174
Information Content of Modalities	p. 176
Monomodal Systems Recognizing Affective Face or Body Movement	p. 177
Multimodal Systems Recognizing Affect from Face and Body Movement	p. 179
Project 1: Multimodal Affect Analysis for Future Cars	p. 179
Project 2: Emotion Analysis in Man-Machine Interaction Systems	p. 182
Project 3: Multimodal Affect Recognition in Learning Environments	p. 183
Project 4: FABO-Fusing Face and Body Gestures for Bimodal Emotion Recognition	p. 184
Multimodal Affect Systems: The Future	p. 185
References	p. 187
Importance of Vision in Human-Robot Communication: Understanding Speech Using Robot Vision and Demonstrating Proper Actions to Human Vision	p. 191
Introduction	p. 191
Understanding Simplified Utterances Using Robot Vision	p. 193
Inexplicit Utterances	p. 193
Information Obtained by Vision	p. 194
Language Processing	p. 195
Vision Processing	p. 195
Synchronization Between Speech and Vision	p. 197
Experiments	p. 199
Communicative Head Gestures for Museum Guide Robots	p. 200
Observations from Guide-Visitor Interaction	p. 201
Prototype Museum Guide Robot	p. 203
Experiments at a Museum	p. 206
Conclusion	p. 208
References	p. 209
Index	p. 211
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