Real Time Tracking of Multiple Skin Colored Objects with a Possibly Moving Camera 1st edition by Antonis Argyros, Manolis Lourakis ISBN 3540219828 9783540219828

Real-Time Tracking of Multiple Skin-Colored Objects with a Possibly Moving Camera 1st edition by Antonis A. Argyros, Manolis I. A. Lourakis – Ebook PDF Instant Download/Delivery. 3540219828, 978-3540219828
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Product details:

ISBN 10:       3540219828
ISBN 13: 978-3540219828
Author:         Antonis A. Argyros, Manolis I. A. Lourakis
 

Real-Time Tracking of Multiple Skin-Colored Objects with a Possibly Moving Camera 1st Table of contents:

1. Introduction

   • 1.1 Motivation for Tracking Skin-Colored Objects
   • 1.2 Challenges in Real-Time Object Tracking
   • 1.3 The Impact of Camera Motion on Tracking Accuracy
   • 1.4 Contributions of the Paper
   • 1.5 Structure of the Paper

2. Related Work

   • 2.1 Skin Color Segmentation Techniques
   • 2.2 Object Tracking in Static Environments
   • 2.3 Tracking Under Moving or Dynamic Cameras
   • 2.4 Real-Time Object Tracking Approaches
   • 2.5 Limitations of Existing Methods and Gaps in the Literature

3. Problem Definition

   • 3.1 Skin-Colored Object Tracking: A Formulation
   • 3.2 Assumptions and Constraints
   • 3.3 Overview of Tracking Challenges in a Moving Camera Setup
   • 3.4 Real-Time Requirements for Tracking Systems

4. Skin Color Modeling and Segmentation

   • 4.1 Color Spaces for Skin Detection (RGB, YCbCr, HSV)
   • 4.2 Statistical Models for Skin Color
   • 4.3 Adaptive Thresholding for Real-Time Segmentation
   • 4.4 Handling Lighting Variations and Shadows
   • 4.5 Skin Color Detection in Diverse Environmental Conditions

5. Real-Time Object Tracking Framework

   • 5.1 Overview of the Tracking Approach
   • 5.2 Feature Extraction for Object Localization
   • 5.3 Motion Models for Skin-Colored Objects
   • 5.4 Handling Occlusions and Multiple Objects
   • 5.5 Integration of Object Detection and Tracking Modules
   • 5.6 Real-Time Performance Considerations

6. Dealing with Camera Motion

   • 6.1 Types of Camera Motion (Translation, Rotation, Zoom)
   • 6.2 Visual Odometry for Camera Motion Estimation
   • 6.3 Compensating for Camera Motion in Object Tracking
   • 6.4 Robustness of the Tracking Algorithm Under Camera Movement
   • 6.5 Techniques for Stabilizing Tracking in Dynamic Environments

7. Algorithm Design and Optimization

   • 7.1 Tracking Algorithm for Skin-Colored Objects
   • 7.2 Use of Kalman Filters and Particle Filters for Object Prediction
   • 7.3 Multi-Object Tracking and Association
   • 7.4 Optimization for Real-Time Processing: Parallelization and Hardware Acceleration
   • 7.5 Error Handling and Model Updates

8. Experimental Setup

   • 8.1 Datasets and Test Scenarios for Evaluation
   • 8.2 Performance Metrics for Tracking Accuracy (e.g., Intersection-over-Union, Precision, Recall)
   • 8.3 Hardware and Software Platforms Used
   • 8.4 Setup for Moving Camera Simulations
   • 8.5 Ground Truth and Annotations for Evaluation

9. Results and Discussion

   • 9.1 Quantitative Results: Performance on Static vs. Moving Cameras
   • 9.2 Qualitative Results: Visual Comparisons of Tracking Accuracy
   • 9.3 Real-Time Processing: Latency and Frame Rate Analysis
   • 9.4 Robustness to Environmental Changes (Lighting, Occlusions)
   • 9.5 Comparison with Existing Tracking Methods
   • 9.6 Analysis of Tracking Multiple Skin-Colored Objects Simultaneously

10. Applications of the Proposed Method

• 10.1 Surveillance and Security Systems
• 10.2 Human-Computer Interaction and Gesture Recognition
• 10.3 Augmented Reality and Virtual Reality
• 10.4 Autonomous Vehicles and Robotics
• 10.5 Assistive Technologies for People with Disabilities

11. Challenges and Future Directions

• 11.1 Handling Complex Backgrounds and Cluttered Environments
• 11.2 Improving Tracking Accuracy with Noisy or Low-Resolution Data
• 11.3 Real-Time Tracking for High-Speed Objects
• 11.4 Integrating Deep Learning for Better Skin Detection
• 11.5 Expanding to Non-Skin Colored Object Tracking
• 11.6 Scalability and Generalization to Different Camera Setups

12. Conclusion

• 12.1 Summary of Key Findings
• 12.2 Contributions to Real-Time Tracking with Moving Cameras
• 12.3 Limitations and Areas for Future Research
• 12.4 Closing Remarks

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