Synopsis
Preface. Acknowledgements. Introduction. 1.1. Video content analysis: toward a paradigm shift. 1.2. Toward the meaning of video data: bridging the semantic gap. 1.3. Book objective, scope and overview. Detecting shot boundaries in video. 2.1. Introduction. 2.2. Shot-boundary detection: unraveling the problem. 2.3. Feature extraction. 2.4. Modeling prior information. 2.5. Modeling discriminative information. 2.6. Bayesian approach to decision module design. 2.7. Remarks and recommendations. 2.8. References and further reading. Parsing a video into semantic segments. 3.1. Introduction. 3.2. The principle of content coherence. 3.3. Video parsing based on the content coherence principle. 3.4. Content similarity between clips. 3.5. Audio-assisted video parsing. 3.6. Remarks and recommendations. 3.7. References and further reading. Video indexing and abstraction for retrieval. 4.1. Introduction. 4.2. Video indexing. 4.3. Video content representation for browsing and content preview. 4.4. Remarks and recommendations. 4.5. References and further reading. Affective video content analysis. 5.1. Introduction. 5.2. Dimensional approach to affect. 5.3. Affective video content representation. 5.4. Affective video content modeling. 5.5. Applications. 5.6. Remarks and recommendations. 5.7. References and further reading.
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