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