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

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

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作 者: 任偉 著
出版社: 哈爾濱工程大學(xué)出版社
叢編項(xiàng):
標(biāo) 簽: 人工智能

ISBN: 9787811336115 出版時(shí)間: 2010-05-01 包裝: 平裝
開(kāi)本: 16開(kāi) 頁(yè)數(shù): 212 字?jǐn)?shù):  

內(nèi)容簡(jiǎn)介

  《時(shí)空視頻檢索》重點(diǎn)挖掘了視頻的時(shí)空關(guān)系,探索了利用機(jī)器學(xué)習(xí)的方法進(jìn)行視頻切割、語(yǔ)義分類?!稌r(shí)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(shí)空邏輯關(guān)系、視頻的統(tǒng)計(jì)分析方法,研究了如何捕捉視頻的時(shí)空特性,如何利用人工智能神經(jīng)網(wǎng)絡(luò)進(jìn)行視頻切割,如何訓(xùn)練計(jì)算機(jī)“學(xué)會(huì)”用人類的思維進(jìn)行視頻語(yǔ)義分類、檢索。各章節(jié)撰寫排列體現(xiàn)了從簡(jiǎn)到繁、由淺入深、從理論到實(shí)際、從技術(shù)到系統(tǒng)的特點(diǎn)。《時(shí)空視頻檢索》可以作為高等學(xué)校信號(hào)與圖像處理、計(jì)算機(jī)科學(xué)、機(jī)器學(xué)習(xí)、人工智能、機(jī)器視覺(jué)等領(lǐng)域的研究生教材和參考書,也可以作為在這些領(lǐng)域從事相關(guān)工作的高級(jí)科學(xué)技術(shù)人員的參考書。

作者簡(jiǎn)介

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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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