Intelligent distributed video surveillance systems:
Gespeichert in:
Format: | Buch |
---|---|
Sprache: | English |
Veröffentlicht: |
London
Inst. of Electrical Engineers
2006
|
Schriftenreihe: | IEE professional applications of computing series
5 |
Schlagworte: | |
Online-Zugang: | lizenzfrei Publisher description lizenzfrei Inhaltsverzeichnis |
Beschreibung: | XVII, 282 S. Ill., graph. Darst. 24 cm |
ISBN: | 0863415040 9780863415043 |
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Datensatz im Suchindex
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adam_text | IMAGE 1
CONTENTS
FOREWORD XI
AUTHORS AND CONTRIBUTORS XV
1 A REVIEW OF THE STATE-OF-THE-ART IN DISTRIBUTED SURVEILLANCE SYSTEMS 1
M. VALERA AND S. A. VELASTIN
1.1 INTRODUCTION 1
1.2 APPLICATIONS 3
1.3 TECHNIQUES USED IN SURVEILLANCE SYSTEMS 4
1.3.1 OBJ ECT DETECTION 5
1.3.2 OBJECT RECOGNITION, TRACKING AND PERFORMANCE EVALUATION 7
1.3.3 BEHAVIOURAL ANALYSIS 8
1.3.4 DATABASE 9
1.4 REVIEW OF SURVEILLANCE SYSTEMS 10
1.4.1 THIRD GENERATION SURVEILLANCE SYSTEMS 10
1.4.2 GENERAL REQUIREMENTS OF THIRD GENERATION OF SURVEILLANCE SYSTEMS
10
1.4.3 EXAMPLES OF SURVEILLANCE SYSTEMS 11
1.5 DISTRIBUTION, COMMUNICATION AND SYSTEM DESIGN 22
1.6 CONCLUSIONS 23
ACKNOWLEDGEMENTS 24
REFERENCES 24
2 MONITORING PRACTICE: EVENT DETECTION AND SYSTEM DESIGN 31
M. S. SVENSSON, C. HEATH AND P. LUFF
2.1 INTRODUCTION 31
2.2 SETTING THE SCENE: OPERATION ROOMS 33
2.3 REVEALING PROBLEMS 34
IMAGE 2
VI
CONTENTS
2.4 OFF-THE-WORLD 36
2.5 COMBINING VIEWS 37
2.6 TRACKING PROBLEMS: COORDINATING ACTIVITIES 39
2.7 DEPLOYING IMAGE PROCESSING SYSTEMS: IMPLICATIONS FOR DESIGN 43 2.7.1
DRAWING UPON LOCAL KNOWLEDGE 44
2.7.2 COMBINING IMAGES AND DATA 47
2.7.3 DISPLAYING EVENTS: REVEALING PROBLEMS 49
2.8 SUMMARY AND CONCLUSION 52
ACKNOWLEDGEMENTS 53
REFERENCES 54
A DISTRIBUTED DATABASE FOR EFFECTIVE MANAGEMENT AND EVALUATION OF CCTV
SYSTEMS 55
J. BLACK, T. ELLIS AND D. MAKRIS
3.1 INTRODUCTION 55
3.2 BACKGROUND 56
3.2.1 MULTI-VIEW TRACKING SYSTEMS 56
3.2.2 VIDEO ANNOTATION AND EVENT DETECTION 56
3.2.3 SCENE MODELLING 59
3.3 OFF-LINE LEARNING 60
3.3.1 SEMANTIC SCENE MODEIS 60
3.3.2 CAMERA TOPOLOGY 61
3.4 DATABASE DESIGN 61
3.4.1 DATA ABSTRACTION AND REPRESENTATION 61
3.5 VIDEO SUMMARIES AND ANNOTATION 66
3.6 PERFORMANCE EVALUATION 70
3.7 PSEUDO-SYNTHETIC VIDEO 72
3.7.1 GROUND TRUTH TRACK SELECTION 73
3.7.2 PSEUDO-SYNTHETIC VIDEO GENERATION 74
3.7.3 PERCEPTUAL COMPLEXITY 77
3.7.4 SURVEIILANCE METRICS 78
3.8 EXPERIMENTS AND EVALUATION 81
3.8.1 SINGLE-VIEW TRACKING EVALUATION (QUALITATIVE) 81
3.8.2 SINGLE-VIEW TRACKING EVALUATION (QUANTITATIVE) 82
3.9 SUMMARY 87
REFERENCES 87
A DISTRIBUTED DOMOTIC SURVEIILANCE SYSTEM 91
R. CUCCHIARA, C. GRANA, A. PRATI AND R. VEZZANI
4.1 INTRODUCTION 91
4.2 PEOPLE SEGMENTATION FOR IN-HOUSE SURVEIILANCE 95
4.3 PEOPLE TRACKING HANDLING OCCLUSIONS 98
IMAGE 3
CONTENTS VII
5.1 5.2 5.3
INTRODUCTION OBJECTIVES SYSTEM OVERVIEW AND DESCRIPTION OF COMPONENTS
5.3.1
5.3.2 5.3.3 5.3.4 5.3.5
HARDWARE ACQUISITION CODEC NETWORK
STORAEE
4.4 POSTURE CLASSIFICATION IN DEFORMABLE MODEIS WITH TEMPORAL COHERENCE
102
4.4.1 SUPPORT POINT TRACKING 105
4.4.2 TEMPORAL COHERENCE POSTURE CLASSIFIER 107
4.5 MULTI-CAMERA SYSTEM MANAGEMENT 108
4.6 UNIVERSAL MULTIMEDIA ACCESS TO INDOOR SURVEILLANCE DATA 112
4.7 CONCLUSIONS 114
REFERENCES 1 17
A GENERAL-PURPOSE SYSTEM FOR DISTRIBUTED SURVEILLANCE AND COMMUNICATION
121
X. DESURMONT, A. BASTIDE, J. CZYZ, C. PARISOT, J-F. DELAIGLE AND B. MACQ
121 122 123 124 125 125 125
125
5.4 SOFTWARE ARCHITECTURE AND MIDDLEWARE 126
5.4.1 CONTEXT 126
5.4.2 BASIC ARCHITECTURE AND CONCEPT 126
5.4.3 SYSTEM AND MIDDLEWARE INTEGRATION 128
5.5 COMPUTER VISION 131
5.5.1 CONTEXT ACQUISITION 132
5.5.2 IMAGE PRE-FILTERING 134
5.5.3 BOTTOM-UP TRACKING 135
5.5.4 TOP-DOWN TRACKING 143
5.5.5 TRACKING ANALYSIS AND EVENT GENERATION 147
5.5.6 METADATA INFORMATION 147
5.5.7 SUMMARY 148
5.6 RESULTS AND PERFORMANCE 149
5.7 APPLICATION CASE STUDY 151
5.8 CONCLUSIONS 152
ACKNOWLEDGEMENTS 152
REFERENCES 153
TRACKING OBJECTS ACROSS UNCALIBRATED, ARBITRARY TOPOLOGY CANIERA
NETWORKS 157
R. BOWDEN, A. GILBERT AND P. KAEWTRAKULPONG
6.1 INTRODUCTION 157
6.2 PREVIOUS WORK 158
IMAGE 4
VIII CONTENTS
6.3 OVERVIEW 159
6.4 OBJECT DETECTION MODULE 161
6.4.1 BACKGROUND MODELLING 161
6.4.2 SHADOW ELIMINATION 163
6.5 OBJECT TRACKING MODULE 163
6.5.1 TARGET MODEL 164
6.5.2 DATA ASSOCIATION MODULE 164
6.5.3 STOCHASTIC SAMPLING SEARCH 167
6.5.4 TRAJECTORY MAINTENANCE MODULE 167
6.6 COLOUR SIMILARITY 168
6.7 RELATING POSSIBLE REAPPEARING TARGETS 170
6.7.1 PATH EXTRACTION 172
6.7.2 LINKINGPATHS 172
6.8 PATH-BASED TARGET RECOGNITION 174
6.9 LEARNING AND RECOGNISING TRAJECTORY PATTERNS ACROSS CAMERA VIEWS 177
6.10 SUMMARY AND CONCLUSIONS 182
REFERENCES 182
A DISTRIBUTED MULTI-SENSOR SURVEILLANCE SYSTEM FOR PUBLIC TRANSPORT
APPLICATIONS 185
J-L. BRUYELLE, L. KHOUDOUR, D. AUBERT, T. LECLERCQ AND A. FLANCQUART
7.1 INTRODUCTION 185
7.1.1 GENERAL ARCHITECTURE OFTHE SYSTEM 186
7.2 APPLICATIONS 187
7.2.1 INCIDENT DETECTION FUNCTIONS 187
7.2.2 PASSENGER FLOW MEASUREMENT FUNCTIONS 187
7.3 INTRUSIONS INTO FORBIDDEN OR DANGEROUS AREAS 187
7.3.1 CAMERA SET-UP - DEFINING THE COVERED AREA 188
7.3.2 EXTRACTING THE MOVING OBJECTS 188
7.3.3 DEFINING THE SIZE OF OBJECTS 190
7.3.4 FORBIDDEN AREA 191
7.3.5 USAGE OF THE NETWORK 192
7.3.6 TESTRESULTS 193
7.3.7 CONCLUSION 197
7.4 COUNTING OF PASSENGERS 198
7.4.1 COUNTING SYSTEM OVERVIEW 198
7.4.2 PRINCIPLE OFTHE COUNTING SYSTEM 199
7.4.3 PASSENGERS COUNTING 200
7.4.4 LINE IMAGES SEQUENCE OF PEDESTRIANS 200
7.4.5 ALGORITHM USING STRUCTURING ELEMENTS OF VARYING SIZE AND SHAPE 201
7.4.6 IMPLEMENTING THE SYSTEM 202
IMAGE 5
CONTENTS IX
7.4.7 RESULTS 204
7.4.8 IMPLICATIONS AND FUTURE DEVELOPMENTS 208
7.5 DETECTION OF ABNORMAL STATIONARITY 209
7.5.1 INTRODUCTION 209
7.5.2 STATIONARITY DETECTION SYSTEM 210
7.5.3 STATIONARITY DETECTION ALGORITHM 213
7.5.4 RESULTS 215
7.6 QUEUE LENGTH MEASUREMENT 216
7.6.1 INTRODUCTION 216
7.6.2 THE QUEUE MEASUREMENT SYSTEM 217
7.6.3 RESULTS 221
7.7 CONCLUSION 222
ACKNOWLEDGEMENTS 223
REFERENCES 224
8 TRACKING FOOTBALL PLAYERS WITH MULTIPLE CAMERAS 225
D. THIRDE, M. XU AND J. ORWELL
8.1 INTRODUCTION 225
8.2 SYSTEM ARCHITECTURE 227
8.2.1 ARRANGEMENT OF SYSTEM COMPONENTS 227
8.2.2 SYNCHRONOUS FEATURE SETS 229
8.2.3 FORMAT OF FEATURE DATA 230
8.3 VIDEO PROCESSING 230
8.3.1 FOREGROUND DETECTION 230
8.3.2 SINGLE-VIEW TRACKING 234
8.3.3 CATEGORY CLASSIFICATION 236
8.4 MULTI-VIEW, MULTI-PERSON TRACKING 237
8.4.1 ASSOCIATING TARGETS AND FEATURES 237
8.4.2 TARGET INITIALISATION 239
8.5 STRATEGIES FOR SELECTION AND CLASSIFICATION OF TRACKS 240
8.5.1 APPLICATION REQUIREMENTS 241
8.5.2 THE MAP LABELLING HYPOTHESIS 242
8.5.3 ESTIMATES FOR TARGET CATEGORIES 243
8.5.4 LOCAL FIXED POPULATION CONSTRAINTS 244
8.5.5 TECHNIQUES FOR ERROR DETECTION AND CORRECTION 246
8.6 RESULTS 247
8.7 CONCLUSIONS 250
ACKNOWLEDGEMENTS 251
REFERENCES 251
9 A HIERARCHICAL MULTI-SENSOR FRANIEWORK FOR EVENT DETECTION IN WIDE
ENVIRONMENTS 253
G. L. FORESTI, C. MICHELONI, L. SNIDARO AND C. PICIARELLI
9.1 INTRODUCTION 253
IMAGE 6
CONTENTS
9.2 9.3 9.4
9.5 9.6
SYSTEM DESCRIPTION ACTIVE TRACKING STATIC CAMERA NETWORKS 9.4.1 TARGET
TRACKING 9.4.2 POSITION FUSION 9.4.3 TRAJECTORY FUSION EVENT RECOGNITION
CONCLUSIONS REFERENCES
EPILOGUE S.A. VELASTIN
254 256 261 261 263 266 266 268 268
271
INDEX 277
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spellingShingle | Intelligent distributed video surveillance systems IEE professional applications of computing series Maschinelles Sehen (DE-588)4129594-8 gnd Videoüberwachung (DE-588)4758780-5 gnd |
subject_GND | (DE-588)4129594-8 (DE-588)4758780-5 (DE-588)1071861417 (DE-588)4143413-4 |
title | Intelligent distributed video surveillance systems |
title_auth | Intelligent distributed video surveillance systems |
title_exact_search | Intelligent distributed video surveillance systems |
title_full | Intelligent distributed video surveillance systems ed. by Sergio A. Velastin ... |
title_fullStr | Intelligent distributed video surveillance systems ed. by Sergio A. Velastin ... |
title_full_unstemmed | Intelligent distributed video surveillance systems ed. by Sergio A. Velastin ... |
title_short | Intelligent distributed video surveillance systems |
title_sort | intelligent distributed video surveillance systems |
topic | Maschinelles Sehen (DE-588)4129594-8 gnd Videoüberwachung (DE-588)4758780-5 gnd |
topic_facet | Maschinelles Sehen Videoüberwachung Konferenzschrift Aufsatzsammlung |
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