Registration and recognition in images and videos:
Gespeichert in:
Weitere Verfasser: | |
---|---|
Format: | Buch |
Sprache: | English |
Veröffentlicht: |
Berlin [u.a.]
Springer
2014
|
Schriftenreihe: | Studies in computational intelligence
532 |
Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis Klappentext |
Beschreibung: | XI,281 S. Ill., graph. Darst. |
ISBN: | 9783642449062 |
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Datensatz im Suchindex
_version_ | 1804151774223794176 |
---|---|
adam_text | CONTENTS
THE VISUAL FIELD: SIMULTANEOUS ORDER IN IMMEDIATE VISUAL
AWARENESS 1
JAN KOENDERINK, ANDREA VAN DOOM, WHITMAN RICHARDS
1 INTRODUCTION 1
2 LOCAL SIGN 2
3 THE FUZZY LINE 3
4 THE FUZZY PLANE 6
5 ATLAS STRUCTURE: THE SELF-SIMILAR FUZZY LINE AND PLANE 7
5.1 THE SELF-SIMILAR FUZZY PLANE AS A SAMPLING STRUCTURE
IN PHYSIOLOGY 11
5.2 THE SELF-SIMILAR FUZZY PLANE AS A MODEL OF THE
MICROGENESIS OF VISUAL PRESENTATIONS 12
6 METAMERIC IMAGES IN THE FUZZY SELF-SIMILAR PLANE 13
7 THE POINTLESS ORDER 14
7.1 AWARENESS AND HALLUCINATION 19
8 CONCLUSIONS 20
REFERENCES 24
A PRIMER FOR COLOUR COMPUTER VISION 29
GRAHAM D. FINLAYSON
1 COLOUR IMAGE FORMATION 29
1.1 COLOUR CORRECTION 30
2 COLOUR CONSTANCY AND ILLUMINANT ESTIMATION 33
2.1 ESTIMATING THE ILLUMINANT 35
2.2 THE MALONEY WANDELL ALGORITHM 36
2.3 STATISTICAL ILLUMINANT ESTIMATION 38
2.4 EVALUATING ILLUMINANT ESTIMATION ALGORITHMS 38
3 ILLUMINANT INVARIANTS 39
3.1 INTENSITY INVARIANCE 39
3.2 COLOUR INVARIANCE 41
3.3 COMPREHENSIVE NORMALISATION 41
HTTP://D-NB.INFO/1043124047
XIV
CONTENTS
3.4 COLOUR CONSTANCY AT A PIXEL 41
4 COMPUTER VISION AND COLOUR PERCEPTION 43
4.1 COLOUR DIFFERENCE FORMULAE AND COMPUTER VISION (A
CAUTIONARY REMARK) 45
5 CONCLUSION 46
REFERENCES 46
DESCRIPTOR LEARNING FOR OMNIDIRECTIONAL IMAGE MATCHING 49
JONATHAN MASCI, DAVIDE MIGLIORE, MICHAEL M. BRONSTEIN, JIIRGEN
SCHMIDHUBER
1 INTRODUCTION 49
2 BACKGROUND 50
3 SIMILARITY PRESERVING HASHING 51
3.1 SIMILARITY-SENSITIVE HASHING (SSH) 52
3.2 COVARIANCE DIFFERENCE HASHING (DIFF-HASH) 53
3.3 LDAHASH 54
4 NEURAL NETWORK HASHING (NNHASH) 54
5 RESULTS 55
5.1 DATA 55
5.2 METHODS 56
5.3 PERFORMANCE DEGRADATION IN TIME 56
5.4 GENERALIZATION 60
6 DISCUSSION, CONCLUSIONS, AND FUTURE WORK 60
REFERENCES 60
VISUAL CORRESPONDENCE, THE LAMBERT-AMBIENT SHAPE SPACE AND THE
SYSTEMATIC DESIGN OF FEATURE DESCRIPTORS 63
STEFANO SOATTO, JINGMING DONG
1 VISUAL CORRESPONDENCE 63
2 NUISANCE GROUPS, ORBITS AND SHAPE SPACES 66
2.1 EXTENSION TO INFINITE-DIMENSIONAL SHAPE SPACES 73
3 THE GEOMETRY OF THE LAMBERT-AMBIENT MODEL 75
3.1 OCCLUSIONS 79
4 CO-VARIANT DETECTORS, INVARIANT DESCRIPTORS 81
5 AGGREGATING RESIDUAL VARIABILITY 88
6 CONCLUSION 91
REFERENCES 92
CLASSEMES: A COMPACT IMAGE DESCRIPTOR FOR EFFICIENT NOVEL-CLASS
RECOGNITION AND SEARCH 95
LORENZO TORRESANI, MARTIN SZUMMER, ANDREW FITZGIBBON
1 INTRODUCTION 95
2 BACKGROUND 97
3 METHOD OVERVIEW 100
3.1 CLASSEME LEARNING 100
3.2 USING THE CLASSEMES 100
CONTENTS XV
4 FURTHER DETAILS 101
4.1 SELECTING CATEGORY LABELS 101
4.2 GATHERING CATEGORY TRAINING DATA 101
4.3 LEARNING CLASSIFIERS P
C
102
4.4 FEATURE SELECTION 103
4.5 CLASSEME QUANTIZATION 103
5 EXPERIMENTS 103
5.1 EXPERIMENT 1: MULTICLASS CLASSIFICATION 104
5.2 EXPERIMENT 2: RETRIEVAL 106
6 DISCUSSION 109
REFERENCES 109
THE ENHANCED FLOCK OF TRACKERS 113
TOMDS VOJI R, JIN MATAS
1 INTRODUCTION 113
2 RELATED WORK 117
3 TRACKER RELIABILITY PREDICTION METHODS 118
3.1 THE NCC RELIABILITY PREDICTOR P
P
118
3.2 THE FORWARD-BACKWARD RELIABILITY PREDICTOR
PFB
119
3.3 THE NEIGHBOURHOOD CONSISTENCY PREDICTOR P/V 120
3.4 THE MARKOV RELIABILITY PREDICTOR P/V/ 122
4 METHODS FOR COMBINING TRACKER RELIABILITY PREDICTIONS 124
4.1 THE 5? COMBINATION METHOD 124
4.2 THE 3?T COMBINATION METHOD 124
5 RANSAC 125
6 PERFORMANCE EVALUATION 125
6.1 THE TEST DATA 125
6.2 THE EXPERIMENTAL SET-UP 125
6.3 COMPARISON OF SP
A
COMBINATION VS. SP
COMBINATION 127
6.4 COMPARISON OF THE RELIABILITY PREDICTION METHODS 128
6.5 COMPARISON THE SPEED OF THE RELIABILITY PREDICTION
METHODS 129
6.6 ROBUSTNESS TO BOUNDING BOX INITIALIZATION 134
7 CONCLUSIONS 135
REFERENCES 136
REGISTRATION AND SEGMENTATION IN MEDICAL IMAGING 137
DANIEL RUECKERT, JULIA A. SCHNABEL
1 INTRODUCTION 137
2 REGISTRATION 138
3 SEGMENTATION 147
4 PATCH-BASED SEGMENTATION 150
5 SUMMARY AND CONCLUSIONS 152
REFERENCES 153
XVI CONTENTS
CLUSTERING GAMES 157
MARCELLO PELILLO, SAMUEL ROTA BULD
1 INTRODUCTION 157
2 NOTIONS FROM EVOLUTIONARY GAME THEORY 160
3 CLUSTERING AS A NON-COOPERATIVE GAME 162
3.1 INTERNAL COHERENCY 164
3.2 EXTERNAL INCOHERENCY 165
4 EVOLUTION TOWARDS A CLUSTER 166
5 EXPERIMENTS 169
5.1 LINE CLUSTERING 170
5.2 MODEL-BASED 3D POINT-PATTERN MATCHING 173
5.3 OBJECT DETECTION 175
5.4 ILLUMINANT-INVARIANT FACE CLUSTERING 179
6 CONCLUSIONS 181
REFERENCES 183
ABOUT 3D FACES 187
STEFANO BERRETTI, ALBERTO DEL BIMBO, PIETRO PALA
1 INTRODUCTION 187
2 3D FACE ACQUISITION AND PREPROCESSING 192
2.1 LASER SCANNERS 192
2.2 STRUCTURED LIGHT SCANNING 193
2.3 PREPROCESSING 195
3 3D FACE DATASETS AND PERFORMANCE EVALUATION 199
3.1 3D FACE DATASETS 200
3.2 PERFORMANCE INDICATORS 204
4 3D FACE RECOGNITION 205
4.1 COOPERATIVE 3D FACE RECOGNITION 205
4.2 SEMI-COOPERATIVE 3D FACE RECOGNITION 211
4.3 VERY LARGE POSE VARIATIONS 215
5 DISCUSSION 216
REFERENCES 217
SOCIALLY-DRIVEN COMPUTER VISION FOR GROUP BEHAVIOR ANALYSIS 223
MARCO CRISTANI, VITTORIO MURINO
1 ANALYSIS OF SOCIAL INTERACTIONS USING F-FORMATIONS 224
1.1 GROUP INTERACTION DISCOVERY: STATE OF THE ART 225
1.2 A SOCIALLY-DRIVEN METHOD FOR DETECTING GROUP
INTERACTIONS 227
1.3 EXPERIMENTS 229
1.4 SYNTHETIC DATA 230
1.5 REAL SCENARIOS 231
1.6 REMARKS 233
2 INFERRING SOCIAL RELATIONS FROM INTERPERSONAL DISTANCES 233
2.1 FUNDAMENTALS OF PROXEMICS 235
2.2 COMPUTATIONAL PROXEMICS: STATE-OF-THE-ART 237
CONTENTS XVII
2.3 DETECTING A FLEXIBLE SET OF SOCIALLY MEANINGFUL
DISTANCES 238
2.4 TESTING THE FLEXIBLE DISTANCES 239
2.5 REMARKS 244
3 VOICE ACTIVITY DETECTION USING VISUAL CUES IN GROUPS 245
3.1 EXPERIMENTS ON THE VISUAL VAD 247
4 REMARKS 251
5 CONCLUSIONS 252
REFERENCES 252
MOBILE COMPUTATIONAL PHOTOGRAPHY WITH FCAM 257
KARI PULLI, ALEJANDRO TROCCOLI
1 FRANKENCAMERA: AN EXPERIMENTAL PLATFORM FOR COMPUTATIONAL
PHOTOGRAPHY 257
1.1 COMPUTATIONAL PHOTOGRAPHY 257
1.2 FCAM ARCHITECTURE AND API 258
2 CAPTURE CONTROL 259
2.1 SHOTS AND FRAMES 260
2.2 IMAGE BURSTS 261
3 EXTERNAL DEVICES AND SYNCHRONIZATION 261
3.1 DEVICES AND ACTIONS 262
3.2 TAGS 265
3.3 APPLICATION: SECOND-CURTAIN FLASH SYNCHRONIZATION .... 266
4 AUTOMATING CAPTURE PARAMETER SETTING 266
4.1 AUTO EXPOSURE 267
4.2 AUTO FOCUS 269
4.3 AUTO WHITE BALANCE 270
4.4 BUILDING YOUR OWN CAMERA APPLICATION 271
5 FCAM PLATFORMS 272
5.1 THE FCAM RUNTIME 273
5.2 PORTING FCAM 274
6 IMAGE PROCESSING FOR FCAM APPLICATIONS 275
6.1 OPENCV 275
6.2 OPENGL ES 2.0 276
6.3 NEON INTRINSICS 277
6.4 HOW SHOULD YOU CHOOSE WHICH SOLUTION TO USE? 277
7 FCAM IN TEACHING 277
7.1 A BORROWED FLASH 278
7.2 NON-PHOTOREALISTIC VIEWFINDER 279
8 CONCLUSIONS 279
REFERENCES 280
AUTHOR INDEX 283
Computer
vision
is the science and technology of making machines that see. It
is concerned with the theory, design and implementation of algorithms that can
automatically process visual data to recognize objects, track and recover their shape
and spatial layout.
The International Computer Vision Summer School
-
1CVSS was established
in
2007
to provide both an objective and clear overview and an in-depth analysis
of the state-of-the-art research in Computer Vision. The courses are delivered
bv world renowned experts in the field, from both
academia
and industry, and
cover both theoretical and practical aspects ol real Computer Vision problems.
Hie school is organized every year by University of Cambridge (Computer Vision and
Robotics
(¡roup)
and
Universit}7
of Catania (Image Processing Lab), Different topics are
covered each year.This edited volume contains a selection of articles covering some of
the talks and tutorials held during the last editions of the school. The chapters provide
an in-depth overview of challenging areas with kev references to the existing literature.
|
any_adam_object | 1 |
author2 | Cipolla, Roberto 1963- |
author2_role | edt |
author2_variant | r c rc |
author_GND | (DE-588)122160347 |
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dewey-ones | 006 - Special computer methods |
dewey-raw | 006.37 |
dewey-search | 006.37 |
dewey-sort | 16.37 |
dewey-tens | 000 - Computer science, information, general works |
discipline | Maschinenbau / Maschinenwesen Informatik |
format | Book |
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indexdate | 2024-07-10T01:00:09Z |
institution | BVB |
isbn | 9783642449062 |
language | English |
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spelling | Registration and recognition in images and videos Roberto Cipolla ... eds. Berlin [u.a.] Springer 2014 XI,281 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Studies in computational intelligence 532 Bilderkennung (DE-588)4264283-8 gnd rswk-swf Registrierung Bildverarbeitung (DE-588)4778903-7 gnd rswk-swf Maschinelles Sehen (DE-588)4129594-8 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content Maschinelles Sehen (DE-588)4129594-8 s Registrierung Bildverarbeitung (DE-588)4778903-7 s Bilderkennung (DE-588)4264283-8 s DE-604 Cipolla, Roberto 1963- (DE-588)122160347 edt Erscheint auch als Online-Ausgabe 978-3-642-44907-9 Studies in computational intelligence 532 (DE-604)BV020822171 532 DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027029211&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027029211&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA Klappentext |
spellingShingle | Registration and recognition in images and videos Studies in computational intelligence Bilderkennung (DE-588)4264283-8 gnd Registrierung Bildverarbeitung (DE-588)4778903-7 gnd Maschinelles Sehen (DE-588)4129594-8 gnd |
subject_GND | (DE-588)4264283-8 (DE-588)4778903-7 (DE-588)4129594-8 (DE-588)4143413-4 |
title | Registration and recognition in images and videos |
title_auth | Registration and recognition in images and videos |
title_exact_search | Registration and recognition in images and videos |
title_full | Registration and recognition in images and videos Roberto Cipolla ... eds. |
title_fullStr | Registration and recognition in images and videos Roberto Cipolla ... eds. |
title_full_unstemmed | Registration and recognition in images and videos Roberto Cipolla ... eds. |
title_short | Registration and recognition in images and videos |
title_sort | registration and recognition in images and videos |
topic | Bilderkennung (DE-588)4264283-8 gnd Registrierung Bildverarbeitung (DE-588)4778903-7 gnd Maschinelles Sehen (DE-588)4129594-8 gnd |
topic_facet | Bilderkennung Registrierung Bildverarbeitung Maschinelles Sehen Aufsatzsammlung |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027029211&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027029211&sequence=000004&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA |
volume_link | (DE-604)BV020822171 |
work_keys_str_mv | AT cipollaroberto registrationandrecognitioninimagesandvideos |