Semantic segmentation with efficient tree-based methods:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
München
Verl. Dr. Hut
2014
|
| Ausgabe: | 1. Aufl. |
| Schriftenreihe: | Informatik
|
| Schlagworte: | |
| Online-Zugang: | Inhaltstext Inhaltsverzeichnis |
| Beschreibung: | XII, 150 S. Ill., graph. Darst. 210 mm x 148 mm, 254 g |
| ISBN: | 9783843914017 384391401X |
Internformat
MARC
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Datensatz im Suchindex
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|---|---|
| adam_text |
CONTENTS
1 INTRODUCTION 1
1.1 MOTIVATION 1
1.1.1 APPLICATIONS OF SEMANTIC SEGMENTATION 2
1.1.2 CHALLENGES 3
1.2 PREVIOUS WORK 4
1.2.1 PREVIOUS WORK ON RELATED TOPICS 4
1.2.2 PREVIOUS WORK ON SEMANTIC SEGMENTATION 5
1.2.2.1 LOCAL APPEARANCE 5
1.2.2.2 LOCAL CONSISTENCY 6
1.2.2.3 GLOBAL CONSISTENCY 6
1.3 THE IMPORTANCE OF CONTEXTUAL CUES 7
1.4 ANYTIME CLASSIFICATION FOR SEMANTIC SEGMENTATION 9
1.4.1 RELATED WORK ON ANYTIME CLASSIFICATION 9
1.4.2 ANYTIME SEMANTIC SEGMENTATION 11
1.5 CONTRIBUTION AND OUTLINE OF THIS THESIS 11
2 ESSENTIAL FOUNDATIONS 13
2.1 UNSUPERVISED SEGMENTATION METHODS 13
2.1.1 MEAN SHIFT 14
2.1.1.1 MEAN SHIFT CLUSTERING 14
2.1.1.2 MEAN SHIFT SEGMENTATION 15
2.1.2 EFFICIENT GRAPH-BASED IMAGE SEGMENTATION 17
2.2 FEATURE EXTRACTION 18
2.2.1 LOCAL FEATURES 19
2.2.1.1 SIFT FEATURES 20
IX
HTTP://D-NB.INFO/1047257610
2.2.1.2 OPPONENTSIFT*A COLOR EXTENSION OF SIFT . 22
2.2.1.3 3D GEOMETRIC CONTEXT FEATURES 24
2.2.1.4 COLOR NAMES 26
2.2.2 GLOBAL FEATURES 26
2.2.2.1 GAUSSIAN MIXTURE MODEL 27
2.2.2.2 ROBUST ESTIMATION OF A GMM 29
2.3 CLASSIFICATION 30
2.3.1 TREE-BASED CLASSIFIERS 31
2.3.1.1 DECISION TREES 31
2.3.1.2 SPLIT FUNCTION 32
2.3.1.3 RANDOM DECISION FORESTS 32
2.3.2 GAUSSIAN PROCESSES 33
2.3.2.1 BASIC PRINCIPLES OF GAUSSIAN PROCESS PRIORS . . 34
2.3.2.2 PLUG-IN PRINCIPLE 34
2.3.2.3 BAYESIAN FORMULATION FOR REGRESSION AND CLAS
SIFICATION WITH GAUSSIAN PROCESSES 35
2.3.2.4 MULTI-CLASS SCENARIOS USING GAUSSIAN PROCESSES 37
2.3.2.5 PROBABILITY CALIBRATION 37
3 STATE OF THE ART 39
3.1 LOCAL SEMANTIC SEGMENTATION 39
3.1.1 GETTING SPARSE HISTOGRAM FEATURE VECTORS 40
3.1.2 CLASSIFICATION 41
3.1.3 PIXEL-WISE CLASSIFICATION 41
3.1.4 INCORPORATING AN UNSUPERVISED SEGMENTATION 43
3.2 CONTEXT MODEL 44
3.2.1 RANDOM FIELD APPROACHES 44
3.2.2 FURTHER APPROACHES FOR MODELING CONTEXT 45
4 FAST LOCAL SEMANTIC SEGMENTATION WITH GAUSSIAN PROCESSES 47
4.1 LARGE-SCALE GP CLASSIFICATION WITH TREE-BASED MODELS 48
4.1.1 LEARNING 48
4.1.2 PREDICTION 50
4.2 FAST HISTOGRAM INTERSECTION KERNELS FOR GAUSSIAN PROCESSES . 50
4.2.1 FAST KERNEL EVALUATIONS USING HIK 51
4.2.1.1 FAST KERNEL CALCULATION 52
4.2.1.2 QUANTIZATION OF THE FEATURE SPACE 52
X
4.2.2 EFFICIENT GP MULTI-CLASS CLASSIFICATION WITH FAST-HIK
MULTIPLICATIONS 53
4.2.2.1 EFFICIENT COMPUTATION OF WEIGHT VECTOR . 53
4.2.2.2 GENERALIZED HIK 54
4.2.2.3 HANDLING UNBALANCED DATA 54
4.3 SEMANTIC SEGMENTATION FRAMEWORK 54
5 BINARY SEMANTIC SEGMENTATION USING GRABCUT 57
5.1 GRABCUT 57
5.2 C-GRABCUT*CLASSIFICATION OF SEGMENTED IMAGES 59
5.2.1 SEGMENTING WITH PRIOR KNOWLEDGE GMMS 60
5.2.2 CLASSIFICATION 60
5.2.2.1 COLOR INFORMATION 61
5.2.2.2 SHAPE INFORMATION 62
5.2.2.3 FINAL CLASSIFICATION 63
5.3 L-GRABCUT*SEGMENTATION OF CLASSIFIED RECTANGLES 64
6 ITERATIVE CONTEXT FORESTS 65
6.1 RELATED WORK 65
6.2 BUILDING A CONTEXT TREE 66
6.2.1 FEATURE MAPS 67
6.2.2 GENERATING MILLIONS OF FEATURES 67
6.2.3 AUTO CONTEXT FEATURES 69
6.3 ANYTIME CAPABILITY 71
7 EXPERIMENTS AND APPLICATIONS 73
7.1 EVALUATION 73
7.2 DATASETS 74
7.2.1 ETRIMS 75
7.2.2 LABELMEFACADE 75
7.2.3 ECOLE CENTRALE PARIS DATASET 75
7.3 GAUSSIAN PROCESS CLASSIFICATION WITH TREE-BASED MODELS 79
7.3.1 LARGE-SCALE CLASSIFICATION 79
7.3.1.1 MULTI-SENSOR PLACE CLASSIFICATION 79
7.3.1.2 LARGE-SCALE PROBLEMS AND COMPARISON WITH
PREVIOUS WORK 83
7.3.2 RESULTS ON FACADE IMAGES 86
7.3.2.1 EXPERIMENTAL SETUP 86
XI
7.3.2.2 RESULTS AND EVALUATION 88
7.4 GAUSSIAN PROCESSES USING FAST HISTOGRAM INTERSECTION KERNELS FOR
SEMANTIC SEGMENTATION 92
7.5 BINARY SEMANTIC SEGMENTATION USING GRABCUT 94
7.5.1 C-GRABCUT 94
7.5.2 L-GRABCUT 96
7.5.3 DISCUSSION OF RESULTS 98
7.6 ITERATIVE CONTEXT FORESTS 99
7.6.1 APPLICATION ON FACADE IMAGES 99
7.6.1.1 SETTINGS 99
7.6.1.2 RESULTS 102
7.6.1.3 ANYTIME CLASSIFICATION 105
7.6.1.4 EVALUATION OF FEATURE USAGE 105
7.6.1.5 LOOKING BEYOND THE CURRENT HORIZON 108
7.6.2 APPLICATION ON SATELLITE IMAGES 109
7.6.2.1 STUDY AREA AND DATASET 109
7.6.2.2 MODIFICATIONS FOR REMOTE SENSING DATA . 111
7.6.2.3 RESULTS ILL
8 CONCLUSIONS 117
8.1 SUMMARY AND THESIS CONTRIBUTIONS 117
8.2 FUTURE WORK 119
8.2.1 ADAPTIVE RANDOM SAMPLING OF FEATURE TYPES 119
8.2.2 3D SEMANTIC SEGMENTATION 119
8.2.3 NOVELTY DETECTION AND ACTIVE LEARNING 119
8.2.4 COMBINING GP AND ICF 120
8.2.5 MULTIPLE LABELS PER PIXEL 120
8.2.6 FINDING A "PERFECT" SEGMENTATION 121
8.2.7 INCORPORATING SHAPE INFORMATION 121
BIBLIOGRAPHY 123
LIST OF FIGURES 145
LIST OF TABLES 149 |
| any_adam_object | 1 |
| author | Fröhlich, Björn 1984- |
| author_GND | (DE-588)1047549476 |
| author_facet | Fröhlich, Björn 1984- |
| author_role | aut |
| author_sort | Fröhlich, Björn 1984- |
| author_variant | b f bf |
| building | Verbundindex |
| bvnumber | BV041652617 |
| ctrlnum | (OCoLC)870546954 (DE-599)DNB1047257610 |
| dewey-full | 006.37 |
| dewey-hundreds | 000 - Computer science, information, general works |
| 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 | Informatik |
| edition | 1. Aufl. |
| format | Thesis Book |
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| indexdate | 2024-09-10T01:06:51Z |
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| spelling | Fröhlich, Björn 1984- Verfasser (DE-588)1047549476 aut Semantic segmentation with efficient tree-based methods Björn Fröhlich 1. Aufl. München Verl. Dr. Hut 2014 XII, 150 S. Ill., graph. Darst. 210 mm x 148 mm, 254 g txt rdacontent n rdamedia nc rdacarrier Informatik Zugl.: Jena, Univ., Diss., 2013 Bildverstehen (DE-588)4202022-0 gnd rswk-swf Klassifikator Informatik (DE-588)4288547-4 gnd rswk-swf Kontextbezogenes System (DE-588)4739720-2 gnd rswk-swf Bildsegmentierung (DE-588)4145448-0 gnd rswk-swf Merkmalsextraktion (DE-588)4314440-8 gnd rswk-swf Bilderkennung (DE-588)4264283-8 gnd rswk-swf Gauß-Prozess (DE-588)4156111-9 gnd rswk-swf Entscheidungsbaum (DE-588)4347788-4 gnd rswk-swf (DE-588)4113937-9 Hochschulschrift gnd-content Bilderkennung (DE-588)4264283-8 s Bildverstehen (DE-588)4202022-0 s Bildsegmentierung (DE-588)4145448-0 s Merkmalsextraktion (DE-588)4314440-8 s Klassifikator Informatik (DE-588)4288547-4 s Gauß-Prozess (DE-588)4156111-9 s Entscheidungsbaum (DE-588)4347788-4 s Kontextbezogenes System (DE-588)4739720-2 s DE-604 X:MVB text/html http://deposit.dnb.de/cgi-bin/dokserv?id=4586394&prov=M&dok_var=1&dok_ext=htm Inhaltstext DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027093192&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Fröhlich, Björn 1984- Semantic segmentation with efficient tree-based methods Bildverstehen (DE-588)4202022-0 gnd Klassifikator Informatik (DE-588)4288547-4 gnd Kontextbezogenes System (DE-588)4739720-2 gnd Bildsegmentierung (DE-588)4145448-0 gnd Merkmalsextraktion (DE-588)4314440-8 gnd Bilderkennung (DE-588)4264283-8 gnd Gauß-Prozess (DE-588)4156111-9 gnd Entscheidungsbaum (DE-588)4347788-4 gnd |
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| title | Semantic segmentation with efficient tree-based methods |
| title_auth | Semantic segmentation with efficient tree-based methods |
| title_exact_search | Semantic segmentation with efficient tree-based methods |
| title_full | Semantic segmentation with efficient tree-based methods Björn Fröhlich |
| title_fullStr | Semantic segmentation with efficient tree-based methods Björn Fröhlich |
| title_full_unstemmed | Semantic segmentation with efficient tree-based methods Björn Fröhlich |
| title_short | Semantic segmentation with efficient tree-based methods |
| title_sort | semantic segmentation with efficient tree based methods |
| topic | Bildverstehen (DE-588)4202022-0 gnd Klassifikator Informatik (DE-588)4288547-4 gnd Kontextbezogenes System (DE-588)4739720-2 gnd Bildsegmentierung (DE-588)4145448-0 gnd Merkmalsextraktion (DE-588)4314440-8 gnd Bilderkennung (DE-588)4264283-8 gnd Gauß-Prozess (DE-588)4156111-9 gnd Entscheidungsbaum (DE-588)4347788-4 gnd |
| topic_facet | Bildverstehen Klassifikator Informatik Kontextbezogenes System Bildsegmentierung Merkmalsextraktion Bilderkennung Gauß-Prozess Entscheidungsbaum Hochschulschrift |
| url | http://deposit.dnb.de/cgi-bin/dokserv?id=4586394&prov=M&dok_var=1&dok_ext=htm http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=027093192&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT frohlichbjorn semanticsegmentationwithefficienttreebasedmethods |