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Machine Learning Techniques for Adaptive Multimedia Retrieval

Book Description

Machine Learning Techniques for Adaptive Multimedia Retrieval: Technologies Applications and Perspectives disseminates current information on multimedia retrieval, advances the field of multimedia databases, and educates the multimedia database community. It is a critical text for professionals who are engaged in efforts to understand machine learning techniques for adaptive multimedia retrieval research, design and applications.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
    2. List of Reviewers
  5. Preface
  6. Acknowledgment
  7. Section 1:
    1. Chapter 1: Techniques for Content-Based Multimedia Retrieval
      1. ABSTRACT
      2. INTRODUCTION
      3. APPLICATIONS
      4. FRAMEWORK OF CONTENT-BASED RETRIEVAL SYSTEMS
      5. FEATURE EXTRACTION AND REPRESENTATION
      6. DIMENSION REDUCTION OF FEATURE VECTOR
      7. INDEXING
      8. RELEVANCE FEEDBACK
      9. QUERY SPECIFICATIONS
      10. PERFORMANCE EVALUATION
      11. FUTURE RESEARCH ISSUES AND TRENDS
      12. CONCLUSION
    2. Chapter 2: Metrical Properties of Nested Partitions for Image Retrieval
      1. Abstract
      2. INTRODUCTION
      3. STATE OF ART AND BACKGROUND
      4. METRIC ON PARTITION SETS
      5. HIERARCHICAL SET FACTORIZATION
      6. GEOMETRICAL PROPERTIES OF NESTED QUOTIENT SETS
      7. ANALYSIS OF METRICAL RELATIONS BETWEEN NESTED PARTITIONS
      8. EXPERIMENTS AND FUTURE WORK DISCUSSION
    3. Chapter 3: R*-Tree Based Similarity and Clustering Analysis for Images
      1. ABSTRACT
      2. INTRODUCTION
      3. BASICS OF R* TREES
      4. R*-TREE FOR SIMILARITY ANALYSIS
      5. R*TREES FOR CLUSTER ANALYSIS
      6. TOWARD NEXT STEP: ONTOLOGY AND MULTIMEDIA INDEXING
      7. CONCLUSION
    4. Chapter 4: Face Recognition Based on Manifold Learning and SVM Classification of 2D and 3D Geodesic Curves
      1. Abstract
      2. INTRODUCTION
      3. BACKGROUND
      4. HYBRID FACE RECOGNITION USING 2D AND 3D FACIAL DATA
      5. MANIFOLD EMBEDDING OF RADIAL GEODESIC DISTANCES
      6. RESULTS
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
    5. Chapter 5: Trademark Image Retrieval
      1. Abstract
      2. 1. INTRODUCTION
      3. 2. LITERATURE REVIEW
      4. 3. SYSTEM DESIGN AND ARCHITECTURE
      5. 4. SYSTEM IMPLEMENTATION
      6. 5. PERFORMANCE EVALUATION
      7. 6. CONCLUSION
  8. Section 2:
    1. Chapter 6: Discovering Semantics from Visual Information
      1. Abstract
      2. 1. INTRODUCTION
      3. 2. VISUAL INFORMATION REPRESENTATION
      4. 3. ANNOTATION METHODOLOGIES
      5. 4. DATASETS FOR ANNOTATION
      6. 5. SEMANTIC RELEVANCE AMONG CONCEPTS IN VISUAL DOMAIN
      7. 6. SUMMARY
    2. Chapter 7: Collaborative Bayesian Image Annotation and Retrieval
      1. Abstract
      2. I. INTRODUCTION
      3. II. RELATED WORKS
      4. III. THE GENERAL BAYESIAN FRAMEWORK
      5. IV. A BAYESIAN IMAGE ANNOTATION FRAMEWORK
      6. V. A BAYESIAN IMAGE RETRIEVAL FRAMEWORK
      7. VI. EXPERIMENTS
      8. VII. CONCLUSION
    3. Chapter 8: A Highly Scalable and Adaptable Co-Learning Framework on Multimodal Data Mining in a Multimedia Database
      1. Abstract
      2. INTRODUCTION
      3. RELATED WORKD
      4. HIGHLIGHTS OF THIS WORK
      5. CO-LEARNING FRAMEWORK
      6. ADAPTABILITY ANALYSIS
      7. EXPERIMENTAL EVALUATIONS
      8. CONCLUSION
    4. Chapter 9: Non-Topical Classification of Query Logs Using Background Knowledge
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. METHODOLOGY
      5. DISCUSSION
      6. CONCLUSION AND FUTURE RESEARCH
  9. Section 3:
    1. Chapter 10: Temporal-Based Video Event Detection and Retrieval
      1. Abstract
      2. INTRODUCTION
      3. BACKGROUND AND RELATED WORK
      4. PROPOSED FRAMEWORK
      5. EXPERIMENTS
      6. CONCLUSION
    2. Chapter 11: Analyzing Animated Movie Contents for Automatic Video Indexing
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. TEMPORAL SEGMENTATION
      5. COLOR AND ACTION DESCRIPTORS
      6. VIDEO ABSTRACTION
      7. A 3D NAVIGATION SYSTEM ARCHITECTURE
      8. EXPERIMENTAL RESULTS
      9. FUTURE RESEARCH DIRECTIONS
      10. CONCLUSION
    3. Chapter 12: Sports Video Analysis
      1. Abstract
      2. 1. INTRODUCTION
      3. 2. RELATED WORK ON SPORT VIDEO ANALYSIS
      4. 3. TRAJECTORY-BASED BALL TRACKING WITH VISUAL ENRICHMENT IN BROADCAST BASEBALL VIDEO
      5. 4. FUTURE RESEARCH DIRECTIONS
      6. 5. CONCLUSION
  10. Section 4:
    1. Chapter 13: Adaptive Indexing for Semantic Music Information Retrieval
      1. Abstract
      2. INTRODUCTION
      3. BACKGROUND
      4. CURRENT MIR APPROACHES
      5. ADAPTIVE INDEXING APPROACH
      6. EXPERIMENTS ON INDEX CONVERGENCE
      7. CONCLUSION
    2. Chapter 14: Music Content Analysis in MP3 Compressed Domain
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. TEMPO INDUCTION AND BEAT TRACKING ALGORITHMS IN MP3
      5. FREQUENCY ANALYSIS FOR MUSIC SYNCHRONIZATION IN MP3
      6. RESULTS OF THE ALGORITHMS
      7. CONCLUSION
    3. Chapter 15: Acoustic Analysis of Music Albums
      1. Abstract
      2. INTRODUCTION
      3. FEATURE ESTIMATION
      4. AUTOMATIC MUSIC SEGMENTATION
      5. SONG OR CHUNK SEGMENTATION
      6. MUSIC SORTING
      7. CONCLUSION
  11. Compilation of References
  12. About the Contributors
  13. Index