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Visual Object Tracking Using Color and Texture Features Based on Mean-shift and Particle-kalman Filter Algorithm

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Visual Object Tracking Using Color and Texture Features Based on Mean-shift and Particle-kalman Filter Algorithm
論文目錄
 
ABSTRACT第1-11頁
Chapter 1 – Introduction第11-24頁
  1.1 Research Background第11-13頁
  1.2 Overview of Intelligent Video Surveillance System第13頁
  1.3 Important Key Steps in Intelligent Video Surveillance System第13-17頁
    1.3.1 Object detection第15頁
    1.3.2 Object classification第15頁
    1.3.3 Object tracking第15-16頁
    1.3.4 Object analysis第16-17頁
  1.4 The Importance of Object Tracking第17頁
  1.5 Previous Works第17-21頁
  1.6 Research Objectives第21-22頁
  1.7 Structure of the Thesis第22-24頁
Chapter 2 – Challenges in Object Tracking and Several Conventional Object Tracking Algorithms第24-41頁
  2.1 Chapter Introduction第24頁
  2.2 Challenges in Object Tracking第24-26頁
    2.2.1 Illumination variation第24頁
    2.2.2 Non-rigid object第24-25頁
    2.2.3 Non-linear motion第25頁
    2.2.4 Occlusion第25頁
    2.2.5 Background Clutter第25-26頁
    2.2.6 Real-time processing requirement第26頁
  2.3 Features Selection in Object Tracking第26-28頁
    2.3.1 Color feature: RGB and HSV Histogram第26-27頁
    2.3.2 Texture feature: Local Binary Pattern (LBP)第27-28頁
  2.4 Conventional Object Tracking Algorithm第28-36頁
    2.4.1 Mean-shift第28-32頁
    2.4.2 Kalman Filter第32-34頁
    2.4.3 Particle Filter第34-36頁
  2.5 Combination of Conventional Object Tracking Algorithms第36-40頁
    2.5.1 Combination of Mean-shift and Kalman Filter algorithm (MKF)第36-37頁
    2.5.2 Combination of Mean-shift and Particle filter algorithm (MPF)第37-39頁
    2.5.3 Combination of Particle Filter and Kalman Filter algorithm (PKF)第39-40頁
  2.6 Chapter Summary第40-41頁
Chapter 3 - Visual Object Tracking Using Color and Texture Features Based on Mean-shift and Particle-Kalman Filter Algorithm第41-55頁
  3.1 Chapter Introduction第41-43頁
  3.2 Flowchart Diagram of the Proposed Algorithm第43-54頁
    3.2.1 Input第43頁
    3.2.2 Target Model Initialization第43-47頁
    3.2.3 HSV Color Feature based Mean-shift Tracking第47-48頁
    3.2.4 Occlusion Detection第48頁
    3.2.5 Update Target Model第48-49頁
    3.2.6 Color and Texture Features Fusion Based Particle-Kalman Filter Tracking第49-54頁
  3.3 Visual Object Tracking System Implementation第54頁
  3.4 Chapter Summary第54-55頁
Chapter 4 - Experimental Results and Discussions第55-83頁
  4.1 Chapter Introduction第55頁
  4.2 Experimental Environment第55頁
  4.3 Experimental Results第55-82頁
    4.3.1 Qualitative Evaluation and Analysis第55-67頁
    4.3.2 Quantitative Evaluation and Analysis第67-82頁
  4.4 Chapter Summary第82-83頁
Chapter 5 - Conclusion第83-85頁
  5.1 Conclusion and Research Achievements第83-84頁
  5.2 Research Prospects第84-85頁
BIBLIOGRAPHY第85-90頁
ACKNOWLEDGEMENT第90-91頁
附件第91頁

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