声明
摘要
Abstract
Table of contents
List of Figures
List of Tables
List of Abbreviation
Chapter 1 Introduction
1.1 Background
1.2 Terms definition
1.2.1 Areas covered
1.3 Overview and Motivation
1.4 Contribution
1.5 Definition of the problem
1.6 Objectives
1.7 Structure of the thesis
Chapter 2 Background
2.1 Color Space
2.1.1 The RGB Color Spaces
2.1.2 The YUV Color Space
2.1.3 The YIQ Color Space
2.1.4 The YCbCr Color Space
2.2 HSV,HIS and HLS
2.3 Color Match RGB
2.4 Computer Graphics Color Space
2.5 The RGB Color Cube
2.6 Moving object detection
2.7 Discovery comer
2.8 Optical flow
2.9 The SURF
2.10 Local Binary Pattern
2.11 Online Boosting Tracking
2.12 Mean Shift Tracking
2.13 The Background Subtraction
2.14 ViBe Improvement Using New HSV model
2.14.1 Introduction to HSV concept
2.14.2 New model (HSV)
2.14.3 Foreground Segmentation
2.14.4 The Foreground Extraction
2.14.5 Histogram and weighted Ratio
2.15 How Does Compressive Tracking Algorithm Work?
2.16 Random Projection
Chapter 3 Real-Time Tracking for Multiple Objects using RGB Color Space
3.1 Improvement of RGB Color Space
3.2 Proposed Method
3.3 Thresholding
3.5 Experimental Results
3.6 Summary
Chapter 4 Real-Time Tracking for Multiple Objects using Compremive Tracking
4.1 The Key Steps of Compressive Tracking
4.2 Compressive Tracking Techniques
4.2.1 Object Localization
4.2.2 Object Modeling
4.2.3 Manufacture Color Mask
4.2.4 Segmentation
4.2.5 Histogram Back Projection Plan
4.2.6 Result Analysis Method
4.3 Experiments Results
4.3.1 The Implementations
4.3.2 Results and Discussions
4.3.3 The choice of HSV parameters
4.3.4 Discussions
4.3.5 Result analysis
4.4 Summary
Chapter 5 Conclusion and Future Work
Future work
References
Research Publications
Acknowledgments
Appendix
