Ambient Intelligence - A Novel Paradigm

by: Gian Luca Foresti, Tim Ellis

Springer-Verlag, 2006

ISBN: 9780387229911 , 240 Pages

2. Edition

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Ambient Intelligence - A Novel Paradigm


 

Contents

7

Preface

9

Foreword

11

1 AMBIENT INTELLIGENCE

14

1. Introduction

14

2. The Essex approach

15

2.1 The iDorm - A Testbed for Ubiquitous Computing and Ambient Intelligence

15

2.2 The iDorm Embedded Computational Artifacts

17

3. Integrating Computer Vision

21

3.1 User Detection

22

3.2 Estimating reliability of detection

24

3.3 Vision in the iDorm

26

4. Conclusions

26

References

26

2 TOWARDS AMBIENT INTELLIGENCE FOR THE DOMESTIC CARE OF THE ELDERLY

28

1. Introduction

28

2. An Integrated Supervision System

29

2.1 E-service Based Integration Schemata

32

3. People and Robot Localization and Tracking System

34

3.1 System architecture and implementation

36

4. The Plan Execution Monitoring System

39

4.1 Representing Contingencies

42

4.2 The Execution Monitor

43

5. Integrating Sensing and Execution Monitoring: a Running Example

46

6. Conclusions and Future Work

49

References

51

3 SCALING AMBIENT INTELLIGENCE

52

1. Ambient Intelligence: the contribution of different disciplines

52

2. I-BLOCKS technology

55

3. Design process

57

4. Scaling Ambient Intelligence at level of compositional devices: predefined activities

58

4.1 Arithmetic training

59

4.2 Storytelling Play Scenario

60

4.3 Linguistic scenario

63

5. Scaling Ambient Intelligence at level of compositional devices: free activities

65

6. Scaling Ambient Intelligence at the level of configurable environments: future scenarios

67

6.1 The Augmented Playground

67

6.2 Self-reconfigurable Robots

70

7. Discussion and conclusions

71

References

73

4 VIDEO AND RADIO ATTRIBUTES EXTRACTION FOR HETEROGENEOUS LOCATION ESTIMATION

76

1. Introduction

76

2. Related work

77

3. Main tasks of Ambient Intelligence systems

78

4. Architecture design

79

4.1 Inspiration

79

4.2 Mapping the Model into an AmI Architecture

81

4.3 Artificial Sensing

82

4.4 Proposed structure

82

5. Context aware systems

84

5.1 Location feature

85

5.2 The formalism

86

5.3 Alignment and Extraction of Video and Radio Object Reports

88

6. Results

93

6.1 The environment

93

6.2 Results for video object extraction

93

6.3 Results for radio object extraction

93

6.4 Alignment results

95

7. Conclusions

95

8. Acknowledgments

96

References

96

5 DISTRIBUTED ACTIVE MULTICAMERA NETWORKS

102

1. Introduction

102

2. Sensing modalities

102

3. Vision for Ambient Intelligence

103

4. Architecture

104

5. Tracking and object detection

105

5.1 Object detection

105

5.2 Tracking

106

5.3 Appearance models

107

5.4 Track data

108

6. Normalization

108

7. Multi-camera coordination

110

8. Multi-scale image acquisition

111

8.1 Active Head Tracking and Face Cataloging

112

8.2 Uncalibrated, multiscale data acquisition

114

8.3 Extensions

115

9. Indexing Surveillance Data

115

9.1 Visualization

116

10. Privacy

116

11. Conclusions

117

References

117

6 A DISTRIBUTED MULTIPLE CAMERA SURVEILLANCE SYSTEM

120

1. Introduction

120

2. System architecture

121

3. Motion detection and single-view tracking

121

3.1 Motion Detection

122

3.2 Scene Models

124

3.3 Target Tracking

125

3.4 Partial Observation

126

3.5 Target Reasoning

129

4. Multi view tracking

133

4.1 Homography Estimation

133

4.2 Least Median of Squares

134

4.3 Feature Matching Between Overlapping Views

135

4.4 3D Measurements

136

4.5 Tracking in 3D

137

4.6 Non-Overlapping Views

139

5. System architecture

142

5.1 Surveillance Database

143

6. Summary

145

7. Appendix

147

7.1 Kalman Filter

147

7.2 Homography Estimation

148

7.3 3D Measurement Estimation

149

References

150

7 LEARNING AND INTEGRATING INFORMATION FROM MULTIPLE CAMERA VIEWS

152

1. Introduction

152

1.1 Semantic Scene Model

154

2. Learning point-based regions

156

3. Learning trajectory-based regions

159

3.1 Route model

159

3.2 Learning algorithm

161

3.3 Segmentation to paths and junctions

162

4. Activity analysis

163

5. Integration of information from multiple views

164

5.1 Multiple Camera Activity Network (MCAN)

166

6. Database

168

6.1 Metadata Generation

171

7. Summary

175

References

175

8 FAST ONLINE SPEAKER ADAPTATION FOR SMART ROOM APPLICATIONS

178

1. Introduction

178

2. Description of the proposed on-line adaptation technique

179

3. Implementation details of proposed approach

183

3.1 Calculation of in an FST framework

183

4. Experimental details and results

185

5. Conclusions

187

References

187

9 STEREO-BASED 3D FACE RECOGNITION SYSTEM FOR AMI

190

1. Introduction

190

2. Face Recognition: Review

192

2.1 Face Recognition from Still Images

192

2.2 Face Recognition from Image Retrievals

193

2.3 3D Face Recognition

194

2.4 NIVA System Overview

195

3. NIVA 3D Vision System

195

3.1 NIVA 3D Stereo-based Face Database

196

4. Face Recognition in NIVA

196

4.1 Fisher/Linear Discriminant Analysis

197

4.2 Face Classification in NIVA

198

4.3 Pattern Vectors

198

5. NIVA Dynamic Indexing to Database and Recognition

199

6. NIVA Implementation of Indexing and Recognition

199

6.1 Feature Space

200

6.4 Step 2: Face Recognition

202

7. Testing and Results

202

7.1 Indexing and Recognition Performance

203

7.2 Conclusion and Future Work

205

References

209

10 SECURITY AND BUILDING INTELLIGENCE

212

1. Introduction

212

2. System Description

213

3. People tracking and counting

215

3.1 People tracking

215

3.2 People counting

216

4. Event detection and association

217

5. Experimental results

217

6. AmI for training environments

218

7. Conclusions

222

References

223

11 SUSTAINABLE CYBERNETICS SYSTEMS

226

1. Encoding Interplay and Co-Evolution

229

1.1 Encoding Interplay between Natural and Cybernetic Systems

229

1.2 Encoding Co-Evolution of Natural and Cybernetic Systems

236

2. Sustaining Ambient Intelligence

245

2.1 Propagating Structure and Function

245

2.2 Indicators of Sustainability

249

2.3 Collective Intelligent Agents

250

3. Conclusion

250

References

251

Index

252