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List of Figures | ix | |
List of Tables | xiii | |
Preface | xv | |
Acknowledgments | xix | |
Part I | Introduction | |
1. | Introduction | 3 |
1. | Significance of Proposed Research | 3 |
1.1 | Video Segmentation and Annotation | 3 |
1.2 | Audio and Visual Content Analysis | 4 |
1.3 | MPEG-7 Standard Development | 6 |
2. | Review of Previous Work | 8 |
2.1 | Work on Video Indexing and Retrieval | 8 |
2.2 | Work on Audio Content Analysis | 9 |
2.3 | Work on Visual Content Analysis | 12 |
3. | Summary of the Proposed System | 12 |
3.1 | Framework for Video Segmentation and Indexing | 12 |
3.2 | Content Analysis of the Audio Stream | 13 |
3.3 | Content Analysis of Image Sequences | 17 |
4. | Contribution of the Research | 17 |
5. | Outline of the Monograph | 19 |
Part II | Video Content Modeling | |
2. | Video Content Modeling | 23 |
1. | Common Model for Video Content | 23 |
2. | Models for Different Video Types | 24 |
2.1 | News Bulletin | 24 |
2.2 | Variety Show Video | 24 |
2.3 | Sports Video | 25 |
2.4 | Documentaries | 26 |
2.5 | Feature Movies and TV Series | 27 |
3. | Proposed Scheme for Video Content Parsing | 28 |
4. | Design of Index Table for Non-linear Access | 30 |
4.1 | The Primary Index Table | 30 |
4.2 | The Secondary Index Tree | 30 |
Part III | Audio Content Analysis | |
3. | Audio Feature Analysis | 35 |
1. | Audio Features for Coarse-Level Segmentation and Indexing of Generic Data | 35 |
1.1 | Short-Time Energy Function | 35 |
1.2 | Short-Time Average Zero Crossing Rate | 37 |
1.3 | Short-Time Fundamental Frequency | 38 |
1.4 | Spectral Peak Track | 42 |
2. | Audio Features for Fine-Level Classification and Retrieval of Sound Effects | 48 |
2.1 | Timbre Features | 48 |
2.2 | Rhythm Features | 53 |
4. | Generic Audio Data Segmentation and Indexing | 55 |
1. | Detection of Segment Boundaries | 55 |
2. | Classification of Each Segment | 56 |
2.1 | Detecting Silence | 56 |
2.2 | Separating Sounds into with and without Music Components | 58 |
2.3 | Detecting Harmonic Environmental Sounds | 61 |
2.4 | Distinguishing Pure Music | 61 |
2.5 | Distinguishing Songs | 62 |
2.6 | Separating Speech with Music Background and Environmental Sound with Music Background | 62 |
2.7 | Distinguishing Pure Speech | 63 |
2.8 | Classifying Non-harmonic Environmental Sounds | 65 |
3. | Post-Processing | 65 |
5. | Sound Effects Classification and Retrieval | 69 |
1. | Hidden Markov Model and Gaussian Mixture Model | 69 |
1.1 | The Gaussian Mixture Model | 70 |
1.2 | The Hidden Markov Model | 71 |
1.3 | Hidden Markov Model with Continuous Observation Density | 72 |
1.4 | Hidden Markov Model with Explicit State Duration Density | 73 |
2. | Clustering of Feature Vectors | 74 |
3. | Training of HMM Parameter Sets | 75 |
3.1 | The Training Process | 75 |
3.2 | Implementational Issues | 77 |
3.3 | Comparison with the Baum-Welch Method | 79 |
3.4 | Incorporation of the Viterbi Algorithm | 79 |
4. | Classification of Environmental Sound | 80 |
5. | Query-by-Example Retrieval of Environmental Sound | 81 |
Part IV | Image Sequence Analysis | |
6. | Image Sequence Analysis | 85 |
1. | Histogram Difference value in Image Sequences | 85 |
1.1 | Definition of the Metrics | 85 |
1.2 | Histogram Difference of the Y-Component | 86 |
1.3 | Histogram Difference of the U and V Components | 88 |
1.4 | Histogram Difference of the Combined Code | 89 |
2. | The Twin-Comparison Approach | 91 |
2.1 | The Original Algorithm | 91 |
2.2 | Experimental Results and Modifications | 92 |
3. | Shot Change Detection Based on Combined Y- and V-Components | 97 |
3.1 | Determination of the Lower Threshold | 97 |
3.2 | Determination of the Higher Threshold | 98 |
3.3 | Framework of the Proposed Scheme | 99 |
4. | Adaptive Keyframe Extraction and Associated Feature Analysis | 102 |
4.1 | Adaptive Keyframe Extraction | 102 |
4.2 | Feature Analysis of Keyframes | 103 |
Part V | Experimental Results | |
7. | Experimental Results | 107 |
1. | Generic Audio Data Segmentation and Indexing | 107 |
1.1 | Audio Database | 107 |
1.2 | Coarse-Level Classification Results | 108 |
1.3 | Segmentation and Indexing Results | 109 |
2. | Environmental Sound Classification and Retrieval | 112 |
2.1 | Timbre Retrieval with GMM | 112 |
2.2 | Sound Effects Classification Results | 112 |
2.3 | Sound Effects Retrieval Results | 114 |
3. | Shot Change Detection and Keyframe Extraction | 115 |
3.1 | Shot Change Detection Results | 115 |
3.2 | Keyframe Extraction Results | 116 |
4. | Index Table Generation | 117 |
4.1 | Index Table for News Bulletin | 117 |
4.2 | Index Table for Documentary | 119 |
Part VI | Conclusion | |
8. | Conclusion and Extensions | 123 |
1. | Conclusion | 123 |
2. | Feature Extraction in the Compression Domain | 124 |
3. | System Integration and Applications | 125 |
4. | Contributions to MPEG-7 | 126 |
References | 129 | |
Index | 135 |
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Add Content-Based Audio Classification and Retrieval for Audiovisual Data Parsing, Content-Based Audio Classification and Retrieval for Audiovisual Data Parsing is an up-to-date overview of audio and video content analysis. Included is extensive treatment of audiovisual data segmentation, indexing and retrieval based on multimodal media, Content-Based Audio Classification and Retrieval for Audiovisual Data Parsing to the inventory that you are selling on WonderClubX
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Add Content-Based Audio Classification and Retrieval for Audiovisual Data Parsing, Content-Based Audio Classification and Retrieval for Audiovisual Data Parsing is an up-to-date overview of audio and video content analysis. Included is extensive treatment of audiovisual data segmentation, indexing and retrieval based on multimodal media, Content-Based Audio Classification and Retrieval for Audiovisual Data Parsing to your collection on WonderClub |