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時空視頻檢索(video retrieval using spatio-temporal infarmation)

時空視頻檢索(video retrieval using spatio-temporal infarmation)

定 價:¥28.00

作 者: 任偉 著
出版社: 哈爾濱工程大學出版社
叢編項:
標 簽: 人工智能

ISBN: 9787811336115 出版時間: 2010-05-01 包裝: 平裝
開本: 16開 頁數(shù): 212 字數(shù):  

內容簡介

  《時空視頻檢索》重點挖掘了視頻的時空關系,探索了利用機器學習的方法進行視頻切割、語義分類。《時空視頻檢索》分七章,闡明了圖像的各種特性,論述了視頻的特征,系統(tǒng)介紹了視頻的時空邏輯關系、視頻的統(tǒng)計分析方法,研究了如何捕捉視頻的時空特性,如何利用人工智能神經(jīng)網(wǎng)絡進行視頻切割,如何訓練計算機“學會”用人類的思維進行視頻語義分類、檢索。各章節(jié)撰寫排列體現(xiàn)了從簡到繁、由淺入深、從理論到實際、從技術到系統(tǒng)的特點?!稌r空視頻檢索》可以作為高等學校信號與圖像處理、計算機科學、機器學習、人工智能、機器視覺等領域的研究生教材和參考書,也可以作為在這些領域從事相關工作的高級科學技術人員的參考書。

作者簡介

暫缺《時空視頻檢索(video retrieval using spatio-temporal infarmation)》作者簡介

圖書目錄

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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