Background Subtraction Based on Robust Principle Component A
發(fā)布時間:2020-12-31 02:23
本文中,我基于現(xiàn)有的魯棒性主成分分析算法提出了一個基于魯棒性主成分分析的在線算法并描述了它的GPU實現(xiàn)和優(yōu)化。全文一共有四個部分:緒論、理論基礎(chǔ)、新算法的提出和新算法的GPU實現(xiàn)方法。第一部分中文章主要介紹了背景提取的概念、研究意義和研究現(xiàn)狀。第二部分從背景提取的基本步驟和方法講起,然后到基于主成分分析的背景提取算法到基于魯棒主成分分析的背景提取算法的發(fā)展進化歷程。新算法的提出部分我主要介紹了新算法的整體框架和一些具體的實現(xiàn)細節(jié)。在最后一部分GPU實現(xiàn)方法部分中,我介紹了如何將新的在線魯棒性主成分分析算法通過CUDA技術(shù)來實現(xiàn)在GPU上的運行和優(yōu)化。隨著人工智能的不斷發(fā)展,對機器視覺的需求也越來越大。而對于任何機器人來說,獲取視覺信息的最便宜最直接的方式就是使用視頻。目前,視頻和攝像機已經(jīng)被使用在視頻游戲,安全監(jiān)控,人體健康檢測等諸多領(lǐng)域。對智能機器人來說,最重要的不是對視頻的提取,而是通過機器的處理去理解視頻中的各種元素。這就需要視頻中運動對象的識別和分離,也就是對視頻的前后景的分離:對視頻中的圖像序列進行分析和處理,檢測或者識別視頻中的運動的對象然后提取出視頻中的完整的背景信息。因...
【文章來源】:華中師范大學湖北省 211工程院校 教育部直屬院校
【文章頁數(shù)】:69 頁
【學位級別】:碩士
【文章目錄】:
acknowledgement
abstract
Nomenclature
Chapter 1 Introduction
1.1 Background
1.2 Research significance
1.3 State of the arts
1.4 Thesis structure
Chapter 2 Background subtraction
2.1 Introduction to background subtraction
2.2 Assumptions in background subtraction
2.3 Steps in background subtraction
2.4 Traditional approaches in background subtraction
Chapter 3 From PCA to RPCA
3.1 Introduction
3.2 Principle Component Analysis
3.3 Robust Principle Component Analysis
3.4 Traditional algorithm for solving RPCA
3.4.1 IT algorithm
3.4.2 APG algorithm
3.4.3 ALM algorithm
Chapter 4 Background modelling by RPCA
4.1 Main point of work in this chapter
4.2 RPCA for background subtraction
4.3 General model of Online Robust PCA with Initialization
4.4 Batch step
4.4.1 ADMM algorithm
4.4.2 Noise reduction
4.5 Online RPCA with Initialization
4.6 Experiments and evaluation
Chapter 5 Implementation and optimisation using CUDA
5.1 Main point of work in this chapter
5.2 Introduce to CUDA
5.3 GPU programming basics
5.4 Algorithm steps
5.4.1 Parallel computing
5.4.2 Pre-processing
5.4.3 Generate the background model
5.5 Implementation details
5.5.1 Alternating Direction Method of Multipliers algorithm
5.5.2 Online Robust PCA with Initialization algorithm
5.5.3 Other processing
Chapter 6 Summary
Appendix A
References
本文編號:2948761
【文章來源】:華中師范大學湖北省 211工程院校 教育部直屬院校
【文章頁數(shù)】:69 頁
【學位級別】:碩士
【文章目錄】:
acknowledgement
abstract
Nomenclature
Chapter 1 Introduction
1.1 Background
1.2 Research significance
1.3 State of the arts
1.4 Thesis structure
Chapter 2 Background subtraction
2.1 Introduction to background subtraction
2.2 Assumptions in background subtraction
2.3 Steps in background subtraction
2.4 Traditional approaches in background subtraction
Chapter 3 From PCA to RPCA
3.1 Introduction
3.2 Principle Component Analysis
3.3 Robust Principle Component Analysis
3.4 Traditional algorithm for solving RPCA
3.4.1 IT algorithm
3.4.2 APG algorithm
3.4.3 ALM algorithm
Chapter 4 Background modelling by RPCA
4.1 Main point of work in this chapter
4.2 RPCA for background subtraction
4.3 General model of Online Robust PCA with Initialization
4.4 Batch step
4.4.1 ADMM algorithm
4.4.2 Noise reduction
4.5 Online RPCA with Initialization
4.6 Experiments and evaluation
Chapter 5 Implementation and optimisation using CUDA
5.1 Main point of work in this chapter
5.2 Introduce to CUDA
5.3 GPU programming basics
5.4 Algorithm steps
5.4.1 Parallel computing
5.4.2 Pre-processing
5.4.3 Generate the background model
5.5 Implementation details
5.5.1 Alternating Direction Method of Multipliers algorithm
5.5.2 Online Robust PCA with Initialization algorithm
5.5.3 Other processing
Chapter 6 Summary
Appendix A
References
本文編號:2948761
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