Visual Object Tracking using Deep Learning
eBook - ePub

Visual Object Tracking using Deep Learning

  1. 202 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Visual Object Tracking using Deep Learning

About this book

This book covers the description of both conventional methods and advanced methods. In conventional methods, visual tracking techniques such as stochastic, deterministic, generative, and discriminative are discussed. The conventional techniques are further explored for multi-stage and collaborative frameworks. In advanced methods, various categories of deep learning-based trackers and correlation filter-based trackers are analyzed.

The book also:

  • Discusses potential performance metrics used for comparing the efficiency and effectiveness of various visual tracking methods
  • Elaborates on the salient features of deep learning trackers along with traditional trackers, wherein the handcrafted features are fused to reduce computational complexity
  • Illustrates various categories of correlation filter-based trackers suitable for superior and efficient performance under tedious tracking scenarios
  • Explores the future research directions for visual tracking by analyzing the real-time applications

The book comprehensively discusses various deep learning-based tracking architectures along with conventional tracking methods. It covers in-depth analysis of various feature extraction techniques, evaluation metrics and benchmark available for performance evaluation of tracking frameworks. The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

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Yes, you can access Visual Object Tracking using Deep Learning by Ashish Kumar in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Electrical Engineering & Telecommunications. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Half Title page
  3. Title Page
  4. Copyright Page
  5. Contents
  6. Preface
  7. Author bio
  8. Chapter 1 Introduction to visual tracking in video sequences
  9. Chapter 2 Research orientation for visual tracking models: Standards and models
  10. Chapter 3 Saliency feature extraction for visual tracking
  11. Chapter 4 Performance metrics for visual tracking: A qualitative and quantitative analysis
  12. Chapter 5 Visual tracking data sets: Benchmark for evaluation
  13. Chapter 6 Conventional framework for visual tracking: Challenges and solutions
  14. Chapter 7 Stochastic framework for visual tracking: Challenges and solutions
  15. Chapter 8 Multi-stage and collaborative tracking model
  16. Chapter 9 Deep learning-based visual tracking model: A paradigm shift
  17. Chapter 10 Correlation filter-based visual tracking model: Emergence and upgradation
  18. Chapter 11 Future prospects of visual tracking: Application-specific analysis
  19. Chapter 12 Deep learning-based multi-object tracking: Advancement for intelligent video analysis
  20. Index