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时空视频检索(英文版)
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时空视频检索(英文版)
出版时间:2010年版
内容简介
《时空视频检索》重点挖掘了视频的时空关系,探索了利用机器学习的方法进行视频切割、语义分类。《时空视频检索》分七章,阐明了图像的各种特性,论述了视频的特征,系统介绍了视频的时空逻辑关系、视频的统计分析方法,研究了如何捕捉视频的时空特性,如何利用人工智能神经网络进行视频切割,如何训练计算机“学会”用人类的思维进行视频语义分类、检索。各章节撰写排列体现了从简到繁、由浅入深、从理论到实际、从技术到系统的特点。《时空视频检索》可以作为高等学校信号与图像处理、计算机科学、机器学习、人工智能、机器视觉等领域的研究生教材和参考书,也可以作为在这些领域从事相关工作的高级科学技术人员的参考书。
目录
Chapter Ⅰ Introduction
1.1 Motivation
1.2 Proposed Solution
1.3 Structure of Book
Chapter Ⅱ Approaches to Video Retrieval
2.1 Introduction
2.2 Video Structure and Properties
2.3 Query
2.4 Similarity Metrics
2.5 Performance Evaluation Metrics
2.6 Systems
Chapter Ⅲ Spatio-temporal Image and Video Analysis
3.1 Spatio-temporal Information for Video Retrieval
3.2 Spatial Information Modelling in Multimedia Retrieval .
3.3 Temporal Model
3.4 Spatio-temporal Information Fusion
Chapter Ⅳ Video Spatio-temporal Analysis and Retrieval (VSTAR) :A New Model
4.1 VSTAR Model Components
4.2 Spatial Image Analysis
4.3 A Model for the Temporal Analysis of Image Sequences
4.4 Video Representation. Indexing. and Retrieval Usinz VSTAR
4.5 Conclusions
Chapter Ⅴ Two Comparison Baseline Models for Video Retrieval
5.1 Baseline Models "
5.2 Adjeroh et al. (1999) Sequences Matching——Video Retrieval Model
5.3 Kim and Park (2002a) data set matching——Video Retrieval Model
Chapter VI Spatio-temporal Video Retrieval——Experiments and Results
6.1 Purpose of Experiments
6.2 Data Description
6.3 Spatial and Temporal Feature Extraction
6.4 Video Retrieval Models: Procedure for Parameter Optimisation
6.5 Video Retrieval Models:Resuhs on Parameter Optimisation
6.6 Comparison of Four Models
6.7 Model Robustness (Noise)
6.8 Computational Complexity
6.9 Conclusions
Chapter VII Conclusions
7.1 Reflections on the book as a whole
7.2 Support for book statement
7.3 Limitations of the spatio-temporal knowledge-based model
7.4 Directions for further work
Appendix A Compressed vs. Uncompressed Video
Appendix B Video Annotation
B. 1 Semi-automatic Video Annotation System
B. 2 Automatic Annotation by Object Tracking
Appendix C Object-pair Correlation Matrix
Appendix D Key-frames Extraction
D. 1 Feature-based Representation and Similarity Measures .
D. 2 Threshold Selection
Appendix E Audio Features
Reference
出版时间:2010年版
内容简介
《时空视频检索》重点挖掘了视频的时空关系,探索了利用机器学习的方法进行视频切割、语义分类。《时空视频检索》分七章,阐明了图像的各种特性,论述了视频的特征,系统介绍了视频的时空逻辑关系、视频的统计分析方法,研究了如何捕捉视频的时空特性,如何利用人工智能神经网络进行视频切割,如何训练计算机“学会”用人类的思维进行视频语义分类、检索。各章节撰写排列体现了从简到繁、由浅入深、从理论到实际、从技术到系统的特点。《时空视频检索》可以作为高等学校信号与图像处理、计算机科学、机器学习、人工智能、机器视觉等领域的研究生教材和参考书,也可以作为在这些领域从事相关工作的高级科学技术人员的参考书。
目录
Chapter Ⅰ Introduction
1.1 Motivation
1.2 Proposed Solution
1.3 Structure of Book
Chapter Ⅱ Approaches to Video Retrieval
2.1 Introduction
2.2 Video Structure and Properties
2.3 Query
2.4 Similarity Metrics
2.5 Performance Evaluation Metrics
2.6 Systems
Chapter Ⅲ Spatio-temporal Image and Video Analysis
3.1 Spatio-temporal Information for Video Retrieval
3.2 Spatial Information Modelling in Multimedia Retrieval .
3.3 Temporal Model
3.4 Spatio-temporal Information Fusion
Chapter Ⅳ Video Spatio-temporal Analysis and Retrieval (VSTAR) :A New Model
4.1 VSTAR Model Components
4.2 Spatial Image Analysis
4.3 A Model for the Temporal Analysis of Image Sequences
4.4 Video Representation. Indexing. and Retrieval Usinz VSTAR
4.5 Conclusions
Chapter Ⅴ Two Comparison Baseline Models for Video Retrieval
5.1 Baseline Models "
5.2 Adjeroh et al. (1999) Sequences Matching——Video Retrieval Model
5.3 Kim and Park (2002a) data set matching——Video Retrieval Model
Chapter VI Spatio-temporal Video Retrieval——Experiments and Results
6.1 Purpose of Experiments
6.2 Data Description
6.3 Spatial and Temporal Feature Extraction
6.4 Video Retrieval Models: Procedure for Parameter Optimisation
6.5 Video Retrieval Models:Resuhs on Parameter Optimisation
6.6 Comparison of Four Models
6.7 Model Robustness (Noise)
6.8 Computational Complexity
6.9 Conclusions
Chapter VII Conclusions
7.1 Reflections on the book as a whole
7.2 Support for book statement
7.3 Limitations of the spatio-temporal knowledge-based model
7.4 Directions for further work
Appendix A Compressed vs. Uncompressed Video
Appendix B Video Annotation
B. 1 Semi-automatic Video Annotation System
B. 2 Automatic Annotation by Object Tracking
Appendix C Object-pair Correlation Matrix
Appendix D Key-frames Extraction
D. 1 Feature-based Representation and Similarity Measures .
D. 2 Threshold Selection
Appendix E Audio Features
Reference
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