Machine Learning Techniques for Multimedia: Case Studies on Organization and Retrieval (Cognitive Technologies)

Cover......Page 1
Cognitive Technologies......Page 2
Machine Learning\rTechniques for\rMultimedia......Page 3
ISBN: 9783540751700......Page 4
Preface......Page 6
Contents......Page 10
List of Contributors......Page 16
Part I\rIntroduction to Learning Principles\rfor Multimedia Data......Page 19
1\rIntroduction to Bayesian Methods\rand Decision Theory......Page 21
2\rSupervised Learning......Page 39
3\rUnsupervised Learning and Clustering......Page 69
4\rDimension Reduction......Page 109
Part II\rMultimedia Applications......Page 132
5\rOnline Content-Based Image Retrieval\rUsing Active Learning......Page 133
6\rConservative Learning for Object Detectors......Page 157
7\rMachine Learning Techniques\rfor Face Analysis......Page 177
8\rMental Search in Image Databases:\rImplicit Versus Explicit Content Query......Page 207
9\rCombining Textual and Visual Information\rfor Semantic Labeling of Images and Videos......Page 223
10\rMachine Learning for Semi-structured\rMultimedia Documents: Application\rto Pornographic Filtering and Thematic\rCategorization......Page 245
11\rClassification and Clustering of Music for Novel\rMusic Access Applications......Page 267
Index......Page 305