Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Berlin
De Gruyter
2017
|
| Schriftenreihe: | De Gruyter Graduate
|
| Schlagwörter: | |
| Links: | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029860982&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| Umfang: | XI, 300 Seiten Illustrationen, Diagramme |
| ISBN: | 9783110520347 |
Internformat
MARC
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| 245 | 1 | 0 | |a Image engineering |n volume 3 |p Image understanding |c Yu-Jin Zhang |
| 264 | 1 | |a Berlin |b De Gruyter |c 2017 | |
| 300 | |a XI, 300 Seiten |b Illustrationen, Diagramme | ||
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| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-029860982 | |
Datensatz im Suchindex
| DE-BY-TUM_call_number | 0102 DAT 760f 2017 A 4202-3 |
|---|---|
| DE-BY-TUM_katkey | 2284401 |
| DE-BY-TUM_location | 01 |
| DE-BY-TUM_media_number | 040008259652 |
| _version_ | 1821935544187224064 |
| adam_text | Contents
1 Introduction to Image Understanding----1
1.1 The Development of Image Engineering-----1
1.1.1 Review of Basic Concepts and Definitions--1
1.1.2 An Overview of a Closed Image Technology Survey---5
1.1.3 A New Image Engineering Survey Series----5
1.2 Image Understanding and Related Disciplines---9
1.2.1 Image Understanding-----9
1.2.2 Computer Vision----10
1.2.3 Other Related Disciplines--13
1.2.4 Application Domains of Image Understanding----15
1.3 Theory Framework of Image Understanding-----16
1.3.1 The Visual Computational Theory of Marr--16
1.3.2 Improvements for Marr’s Theoretical Framework---24
1.3.3 Discussions on Marr’s Reconstruction Theory---27
1.3.4 Research on New Theoretical Frameworks----30
1.4 Overview of the Book----33
1.5 Problems and Questions-----34
1.6 Further Reading----35
2 Stereo Vision---37
2.1 Modules of Stereo Vision---37
2.1.1 Camera Calibration---37
2.1.2. Image Capture----38
2.1.3 Feature Extraction---38
2.1.4 Stereo Matching----38
2.1.5 Recovering of 3-D Information--39
2.1.6 Post-processing----39
2.2 Region-Based Binocular Matching-----40
2.2.1 Template Matching----40
2.2.2 Stereo Matching----42
2.3 Feature-Based Binocular Matching----44
2.3.1 Basic Methods----44
2.3.2 Matching Based on Dynamic Programming-----47
2.4 Horizontal Multiple Stereo Matching---49
2.4.1 Horizontal Multiple Imaging---49
2.4.2 Inverse-Distance---50
2.5 Orthogonal Trinocular Matching---53
2.5.1 Basic Principles---54
2.5.2 Orthogonal Matching Based on Gradient Classification--
2.6 Computing Subpixel-Level Disparity---62
2.7 Error Detection and Correction----66
2.7.1 Error Detection----66
2.7.2 Error Correction---67
2.8 Probiems and Questions-------70
2.9 Further Reading----71
3 3-D Shape Information Recovery-----72
3.1 Photometric Stereo-----72
3.1.1 Scene Radiance and Image Irradiance-----73
3.1.2 Surface Reflectance Properties----76
3.1.3 Surface Orientation----77
3.1.4 Reflectance Map and Image Irradiance Equation----79
3.1.5 Solution for Photometric Stereo---82
3.2 Structure from Motion----85
3.2.1 Optical Flow and Motion Field---85
3.2.2 Solution to Optical Flow Constraint Equation--86
3.2.3 Optical Flow and Surface Orientation----90
3.3 Shape from Shading-----93
3.3.1 Shading and Shape------93
3.3.2 Gradient Space-----95
3.3.3 Solving the Brightness Equation with One Image---97
3.4 Texture and Surface Orientation----102
3.4.1 Single Imaging and Distortion---103
3.4.2 Recover Orientation from Texture Gradient---105
3.4.3 Determination of Vanishing Points---108
3.5 Depth from Focal Length-----110
3.6 Pose from Three Pixels---111
3.6.1 Perspective ThreePoint Problem-----112
3.6.2 Iterative Solution--112
3.7 Problems and Questions------114
3.8 Further Reading----115
4 Matching and Understanding------116
4.1 Fundamental of Matching------116
4.1.1 Matching Strategy and Groups-----117
4.1.2 Matching and Registration----118
4.2 Object Matching-----120
4.2.1 Measurement of Matching------120
4.2.2 String Matching----123
4.2.3 Matching of Inertia Equivalent Ellipses-123
4.3 Dynamic Pattern Matching-----125
4.3.1 Flowchart of Matching----125
4.3.2 Absolute Patterns and Relative Patterns--
126
4.4 Relation Matching----128
4.5 Graph Isomorphism------132
4.5.1 Fundamentals of the Graph Theory----132
4.5.2 Graph Isomorphism and Matching------135
4.6 Labeling of Line Drawings--137
4.6.1 Labeling of Contours---137
4.6.2 Structure Reasoning----139
4.6.3 Labeling with Sequential Backtracking---140
4.7 Problems and Questions-----141
4.8 Further Reading---143
5 Scene Analysis and Semantic Interpretation----144
5.1 Overview of Scene Understanding-----144
5.1.1 Scene Analysis----145
5.1.2 Scene Perception Layer----145
5.1.3 Scene Semantic Interpretation----147
5.2 Fuzzy Reasoning---148
5.2.1 Fuzzy Sets and Fuzzy Operation---148
5.2.2 Fuzzy Reasoning Methods----150
5.3 Image Interpretation with Genetic Algorithms--153
5.3.1 Principle of Genetic Algorithms--153
5.3.2 Semantic Segmentation and Interpretation----155
5.4 Labeling of Objects in Scene--159
5.4.1 Labeling Methods and Key Elements-----160
5.4.2 Discrete Relaxation Labeling--160
5.4.3 Probabilistic Relaxation Labeling---162
5.5 Scene Classification---163
5.5.1. Bag of Words/Bag of Feature Models----164
5.5.2 pLSA Model----167
5.5.3 LDA Model-----170
5.6 Problems and Questions-----176
5.7 Further Reading---177
6 Multisensor Image Fusion------179
6.1 Overview of Information Fusion----179
6.1.1 Multisensor Information Fusion----180
6.1.2 Sensor Models-----182
6.2 Image Fusion----185
6.2.1 Main Steps of Image Fusion---185
6.2.2 Three Layers of Image Fusion--186
6.2.3 Evaluation of Image Fusion---188
6.3 Pixel-Layer Fusion---193
6.3.1 Basic Fusion Methods----193
6.3.2 Combination of Fusion Methods----195
6.3.3 The Optimal Decomposition Levels----199
6.3.4 Examples of Pixel-Layer Fusion---201
6.4 Feature-Layer and Decision-Layer Fusions----204
6.4.1 Bayesian Methods------204
6.4.2 Evidence Reasoning-----205
6.4.3 Rough Set Methods------208
6.5 Problems and Questions------212
6.6 Further Reading----213
7 Content-Based Image Retrieval----214
7.1 Feature-Based Image Retrieval----214
7.1.1 Color Features---214
7.1.2 Texture Features---216
7.1.3 Shape Features-----218
7.2 Motion-Feature-Based Video Retrieval-----222
7.2.1 Global Motion Features---222
7.2.2 Local Motion Features----223
7.3 Object-Based Retrieval---225
7.3.1 Multilayer Description Model----225
7.3.2 Experiments on Object-Based Retrieval----227
7.4 Video Analysis and Retrieval----229
7.4.1 News Program Structuring------229
7.4.2 Highlight of Sport Match Video---233
7.4.3 Organization of Home Video-------238
7.5 Problems and Questions------244
7.6 Further Reading----246
8 Spatial-Temporal Behavior Understanding-----248
8.1 Spatial-Temporal Technology--------248
8.1.1 New Domain------249
8.1.2 Multiple Layers----249
8.2 Spatial-Temporal Interesting Points-----251
8.2.1 Detection of Spatial Points of Interest-251
8.2.2 Detection of Spatial-Temporal Points of Interest-252
8.3 Dynamic Trajectory Learning and Analysis----254
8.3.1 Automatic Scene Modeling------255
8.3.2 Active Path Learning------257
8.3.3 Automatic Activity Analysis---261
8.4 Action Classification and Recognition---263
8.4.1 Action Classification-----263
8.4.2 Action Recognition-------265
8.5 Modeling Activity and Behavior-----270
8.5.1 Modeling Action----270
8.5.2 Activity Modeling and Recognition--275
8.6 Problems and Questions----281
8.7 Further Reading----282
Answers to Selected Problems and Questions---283
References----287
Index----297
|
| any_adam_object | 1 |
| author | Zhang, Yu-Jin 1954- |
| author_GND | (DE-588)173988539 |
| author_facet | Zhang, Yu-Jin 1954- |
| author_role | aut |
| author_sort | Zhang, Yu-Jin 1954- |
| author_variant | y j z yjz |
| building | Verbundindex |
| bvnumber | BV044460284 |
| classification_rvk | ST 330 |
| ctrlnum | (OCoLC)1002231250 (DE-599)BVBBV044460284 |
| discipline | Informatik |
| format | Book |
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| genre | (DE-588)4123623-3 Lehrbuch gnd-content |
| genre_facet | Lehrbuch |
| id | DE-604.BV044460284 |
| illustrated | Illustrated |
| indexdate | 2024-12-20T18:03:43Z |
| institution | BVB |
| isbn | 9783110520347 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-029860982 |
| oclc_num | 1002231250 |
| open_access_boolean | |
| owner | DE-20 DE-91G DE-BY-TUM DE-92 DE-739 DE-634 DE-12 |
| owner_facet | DE-20 DE-91G DE-BY-TUM DE-92 DE-739 DE-634 DE-12 |
| physical | XI, 300 Seiten Illustrationen, Diagramme |
| publishDate | 2017 |
| publishDateSearch | 2017 |
| publishDateSort | 2017 |
| publisher | De Gruyter |
| record_format | marc |
| series2 | De Gruyter Graduate |
| spellingShingle | Zhang, Yu-Jin 1954- Image engineering Bildanalyse (DE-588)4145391-8 gnd Bildverarbeitung (DE-588)4006684-8 gnd Mustererkennung (DE-588)4040936-3 gnd |
| subject_GND | (DE-588)4145391-8 (DE-588)4006684-8 (DE-588)4040936-3 (DE-588)4123623-3 |
| title | Image engineering |
| title_auth | Image engineering |
| title_exact_search | Image engineering |
| title_full | Image engineering volume 3 Image understanding Yu-Jin Zhang |
| title_fullStr | Image engineering volume 3 Image understanding Yu-Jin Zhang |
| title_full_unstemmed | Image engineering volume 3 Image understanding Yu-Jin Zhang |
| title_short | Image engineering |
| title_sort | image engineering image understanding |
| topic | Bildanalyse (DE-588)4145391-8 gnd Bildverarbeitung (DE-588)4006684-8 gnd Mustererkennung (DE-588)4040936-3 gnd |
| topic_facet | Bildanalyse Bildverarbeitung Mustererkennung Lehrbuch |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=029860982&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV044654967 |
| work_keys_str_mv | AT zhangyujin imageengineeringvolume3 |
Teilbibliothek Mathematik & Informatik
| Signatur: | 0102 DAT 760f 2017 A 4202-3 |
|---|---|
| Exemplar 1 | Ausleihbar Am Standort |