Perspectives on content based multimedia systems:
Gespeichert in:
| Format: | Buch |
|---|---|
| Sprache: | English |
| Veröffentlicht: |
Boston [u.a.]
Kluwer
2000
|
| Schriftenreihe: | The Kluwer international series on information retrieval
9 |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIV, 391 S. Ill., graph. Darst. |
| ISBN: | 0792379446 |
Internformat
MARC
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| 245 | 1 | 0 | |a Perspectives on content based multimedia systems |c by Jian Kang Wu ... |
| 246 | 1 | 3 | |a Perspectives on content-based multimedia systems |
| 264 | 1 | |a Boston [u.a.] |b Kluwer |c 2000 | |
| 300 | |a XIV, 391 S. |b Ill., graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 1 | |a The Kluwer international series on information retrieval |v 9 | |
| 650 | 4 | |a Multimédia | |
| 650 | 4 | |a Multimedia systems | |
| 700 | 1 | |a Wu, Jian-Kang |e Sonstige |4 oth | |
| 830 | 0 | |a The Kluwer international series on information retrieval |v 9 |w (DE-604)BV011555884 |9 9 | |
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| 999 | |a oai:aleph.bib-bvb.de:BVB01-009310221 | ||
Datensatz im Suchindex
| _version_ | 1804128436111802368 |
|---|---|
| adam_text | Contents
Preface xiii
1 Introduction 1
1.1 Technical Issues 2
1.1.1 Inter operability 2
1.1.2 Automatic or semi automatic indexing 3
1.1.3 Fool proof retrieval methods 3
1.2 Content Based Retrieval 4
1.2.1 Basic idea 4
1.2.2 Existing work 4
1.3 Challenges and Solutions 10
1.4 Layout of the Book 12
References 12
2 Formalism of Content based Multimedia Systems 15
2.1 The System Must be User centered 15
2.1.1 Man machine interaction must be extremely friendly 15
2.1.2 Reduce the work and Information overload of users 15
2.2 Content based Multimedia Information System 16
2.2.1 Definitions 17
2.2.2 Challenges in content based retrieval 21
2.2.3 Representation of multimedia objects 23
2.2.4 Multimedia data analysis 24
2.3 Object Recall A New Formalism for Content Based Re¬
trieval 26
2.3.1 Need for formalism of content based retrieval ... 26
2.3.2 Contrast to pattern classification 28
2.3.3 Formalism for content based navigation 30
2.3.4 Formalism for content based retrieval by adaptive
fuzzy concept 31
vi CONTENTS
2.4 A Content Based Similarity Retrieval Formalism ..... 33
2.4.1 Feature measures and similarity functions ..... 33
2.4.2 Training data set and loss function 34
2.5 Learning of Similarity Function • . . 35
2.5.1 Problem statement 35
2.5.2 Related works 36
2.5.3 Learning of simple similarity functions ....... 37
2.5.4 Learning of multi level similarity functions .... 38
2.6 Experimental Results 41
2.6.1 The data set 41
2.6.2 Feature extraction . 41
2.6.3 Within sequence learning 43
2.6.4 Across sequence learning 44
2.7 Conclusions 47
References 47
3 Color Feature Extraction 49
3.1 Color Spaces Selection 49
3.1.1 RGB color space 49
3.1.2 Munsell color System 50
3.1.3 CIE color Systems . 50
3.1.4 HSV color space 51
3.2 Color Measures 52
3.2.1 A brief review of color features 53
3.2.2 The distance method • 55
3.3 Reference Color Table Method 56
3.3.1 The color clustering based method 58
3.3.2 Experimental results 64
3.3.3 Remarks 65
References 66
4 Texture Feature Extraction 69
4.1 Discrete Cosine Transformed Texture 70
4.1.1 Discrete cosine transform 70
4.1.2 Texture feature based on discrete cosine transform 71
4.1.3 Feature vector formation • . 72
4.1.4 Test results . 72
4.2 Wavelet Transformed Texture Feature . 74
4.2.1 Wavelet Transform . 74
4.2.2 Feature vector formation . 75
4.2.3 Performance evaluation and test results 79
CONTENTS vii
4.3 Texture Features Based on Second Moment Matrix .... 82
4.3.1 Performance evaluation and test results 83
4.4 Comparative Study 84
4.4.1 Comparison based on classification 84
4.4.2 Multiple features combination of color and texture 84
4.4.3 Retrieval test 87
References 90
5 Video Processing 93
5.1 Review of Video Processing Techniques 94
5.1.1 Video features 94
5.1.2 Video applications 95
5.1.3 Research areas 96
5.1.4 State of the art review 97
5.2 Content Based Representative Frame Extraction and
Video Summary 100
5.2.1 Definition 100
5.2.2 Related work 101
5.2.3 Extraction of representative frames 102
5.2.4 Application of representative frame extraction tech
nique 114
References 117
6 Object Segmentation 121
6.1 Edge preserved smoothing of features 123
6.1.1 Principle of edge preserved smoothing 123
6.1.2 EPSM for 2D signal 127
6.1.3 Application in color feature 128
6.1.4 Application in texture feature 129
6.2 Segmentation algorithm: clustering and region merging . . 134
6.2.1 Clustering in the feature space 135
6.2.2 Cluster validation for unsupervised segmentation . 138
6.2.3 Markov random field model and Gibbs distribution 145
6.2.4 Region analysis and region merging 152
6.3 Experiment results 156
6.3.1 Experiment setup 156
6.3.2 Experiment results 157
6.3.3 Summary 169
References 170
7 Human Face Detection 173
viii CONTENTS
7.1 Color Segmentation of Faces 174
7.1.1 Chromaticity diagrams 176
7.1.2 Effects of the projection of 3 D color Spaces on chro
maticity diagrams 180
7.1.3 Method for face detection using chromaticity dia¬
grams 184
7.1.4 Experiments 185
7.2 Shape Information As a Cue 188
7.2.1 Geometrie characteristic of face 188
7.2.2 Shape descriptors 190
7.2.3 Experimental results 191
7.3 Face Feature Detection Using DOG Operators 191
7.3.1 The DOG (Difference of Gaussians) Operator ... 191
7.3.2 Face feature detection by DOG Operator 193
7.3.3 Experimental results 194
7.3.4 Discussion 196
7.4 Template based Human Face Detection 198
7.4.1 Overview 198
7.4.2 Normalized face space 199
7.4.3 Dimensionality reduetion 199
7.4.4 Clustering and face template generation 200
7.4.5 Template matching 203
References 206
8 Visual Keywords 209
8.1 Introduction 209
8.2 Related Works 212
8.3 Methodology 214
8.3.1 Typification 215
8.3.2 Description scheme 219
8.3.3 Selection 222
8.3.4 Coding scheme 222
8.4 Image Retrieval 223
8.4.1 Unsupervised learning 224
8.4.2 Learning by instruetion 228
8.5 Image Categorization 234
8.6 Conclusions and Future Directions 236
References 237
9 Puzzy Retrieval 239
9.1 Problem Definition 240
CONTENTS ix
9.1.1 Content based fuzzy retrieval 240
9.1.2 Fuzzy sets over multi dimensional universes .... 242
9.1.3 Fuzzy queries cannot be processed in the feature
space 243
9.1.4 Fuzzy querying of multimedia Information calls for
new technology for its processing 244
9.2 Fuzzy Database Model 246
9.2.1 Extended tuple relation calculus for image retrieval 249
9.3 Fuzzy Query Processing 251
9.3.1 Feature space and fuzzy Space 251
9.3.2 Fuzzy query interface 252
9.3.3 Context model 253
9.3.4 Extraction of the confidence value 254
9.3.5 Incomplete query condition 255
9.3.6 Similarity measure 256
9.3.7 Relevance feedback for query refinement 258
9.4 Learning Fuzzy Membership Functions 258
9.4.1 Need for learning fuzzy membership functions . . . 259
9.4.2 A Fuzzy neuro membership function 262
9.4.3 Training the neural network 263
9.5 Experimental Results of Fuzzy Retrieval 264
9.5.1 Face database indexing and retrieval 264
9.6 Conclusion and Remarks 270
References 270
10 Pace Retrieval 273
10.1 CAFIIR System 274
10.1.1 Data model 277
10.1.2 Indexing of facial images 279
10.1.3 Feature extraction 279
10.1.4 Content based indexing 280
10.2 Content Based Indexing of Multimedia Object 282
10.2.1 Definition 282
10.2.2 Horizontal links 283
10.2.3 A practical example 285
10.2.4 Iconic images construction 286
10.2.5 Content based retrieval using Contlndex 286
10.3 Contlndex Creation by Self organization Neural Networks 287
10.3.1 LEP neural network architecture 289
10.3.2 Fusion of multi modal feature measures 290
10.3.3 Spatial self organization 291
x CONTENTS
10.3.4 Bi directional learning on experiences 293
10.4 Experimental Results 294
10.5 Conclusion and Remarks 300
10.6 Visual Retrieval of Facial Images 300
10.6.1 Facial composition 300
10.6.2 Browsing and similarity retrieval 301
10.7 Descriptive Queries 303
10.7.1 Fuzzy retrieval of facial images 303
10.7.2 Free text retrieval 306
10.8 Further Improvement of Queries 307
10.8.1 Feedback for query refinement 307
10.8.2 Combined query 308
10.9 Implementation and Concluding Remarks 308
References 309
11 System for Trademark Archival and Retrieval 311
11.1 Representation of Trademarks 312
11.2 Segmentation of Trademarks 314
11.2.1 Color segmentation 315
11.3 Capturing Visual Features of Trademark Images 318
11.3.1 Structural description 319
11.3.2 Feature measures 319
U.3.3 Match shape interpretation using fuzzy thesaurus . 322
11.4 Composite Similarity Measures 323
11.5 Evaluation and Learning of Similarity Measures 326
11.5.1 Selection of training and test data sets 326
11.5.2 Learning of similarity functions 326
11.5.3 Evaluating the shape retrieval 328
11.6 Experimental Results 330
11.7 Conclusions 332
fteferences 332
12 Pigital Home Photo Album 335
12.1 Digital photo is becoming populär 335
12.1.1 What do the home users want? 336
12.1.2 User study 1 337
12.1.3 User study 2 339
12.1.4 The gap between ideal and realistic 339
12.2 Object based Indexing and Retrieval 341
12.2.1 Object categories 343
12.2.2 Object modeis 344
CONTENTS xi
12.2.3 System training 345
12.2.4 Image categorization 348
12.2.5 Image retrieval 352
12.2.6 Experimental results 354
References 358
13 Evaluation of Content based Retrieval 361
13.1 Definition of the Problem 361
13.1.1 Retrieval as a function of data and query 362
13.1.2 Definition of benchmarking of multimedia databases 363
13.2 Benchmarking for Content based Systems 364
13.2.1 Benchmarking for database retrieval methods . . . 364
13.2.2 Benchmarking of Information retrieval methods . . 365
13.2.3 Benchmarking links 367
13.2.4 Benchmarks for approximate retrieval methods . . 368
13.2.5 Complete benchmark for multimedia databases . . 380
13.3 Testing Multimedia Databases 380
13.3.1 Scalability with respect to time 381
13.3.2 Scalability with respect to quality 381
13.3.3 Examples of testing and evaluation 383
13.4 Conclusion 386
References 386
Index 389
|
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| illustrated | Illustrated |
| indexdate | 2024-07-09T18:49:13Z |
| institution | BVB |
| isbn | 0792379446 |
| language | English |
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| series | The Kluwer international series on information retrieval |
| series2 | The Kluwer international series on information retrieval |
| spelling | Perspectives on content based multimedia systems by Jian Kang Wu ... Perspectives on content-based multimedia systems Boston [u.a.] Kluwer 2000 XIV, 391 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier The Kluwer international series on information retrieval 9 Multimédia Multimedia systems Wu, Jian-Kang Sonstige oth The Kluwer international series on information retrieval 9 (DE-604)BV011555884 9 HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009310221&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Perspectives on content based multimedia systems The Kluwer international series on information retrieval Multimédia Multimedia systems |
| title | Perspectives on content based multimedia systems |
| title_alt | Perspectives on content-based multimedia systems |
| title_auth | Perspectives on content based multimedia systems |
| title_exact_search | Perspectives on content based multimedia systems |
| title_full | Perspectives on content based multimedia systems by Jian Kang Wu ... |
| title_fullStr | Perspectives on content based multimedia systems by Jian Kang Wu ... |
| title_full_unstemmed | Perspectives on content based multimedia systems by Jian Kang Wu ... |
| title_short | Perspectives on content based multimedia systems |
| title_sort | perspectives on content based multimedia systems |
| topic | Multimédia Multimedia systems |
| topic_facet | Multimédia Multimedia systems |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=009310221&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| volume_link | (DE-604)BV011555884 |
| work_keys_str_mv | AT wujiankang perspectivesoncontentbasedmultimediasystems |