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Computer Science
Computer Vision
Object Tracking
1. Introduction to Object Tracking
2. Fundamental Concepts and Components
3. Single Object Tracking
4. Multiple Object Tracking
5. Key Challenges in Object Tracking
6. Advanced Topics in Tracking
7. Evaluation of Tracking Performance
8. Applications of Object Tracking
6.
Advanced Topics in Tracking
6.1.
Re-Identification for Long-Term Tracking
6.1.1.
Role of Re-ID in Re-acquiring Lost Targets
6.1.1.1.
Matching Lost and Reappearing Objects
6.1.2.
Deep Learning for Person Re-ID
6.1.2.1.
Feature Embedding Networks
6.1.2.2.
Metric Learning Approaches
6.2.
Multi-Camera Tracking
6.2.1.
Camera Calibration and Geometry
6.2.1.1.
Intrinsic Parameters
6.2.1.2.
Extrinsic Parameters
6.2.1.3.
Homography and Transformation
6.2.2.
Inter-camera Trajectory Association
6.2.2.1.
Cross-camera Identity Matching
6.2.2.2.
Spatio-temporal Constraints
6.3.
Tracking in Different Modalities
6.3.1.
Infrared Tracking
6.3.1.1.
Sensor Characteristics
6.3.1.2.
Applications in Low-light Environments
6.3.2.
3D Point Cloud Tracking
6.3.2.1.
Point Cloud Representation
6.3.2.2.
Object Segmentation and Association
6.4.
Unsupervised and Self-Supervised Tracking
6.4.1.
Learning Without Labeled Data
6.4.2.
Self-supervised Objectives
6.4.3.
Domain Adaptation
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5. Key Challenges in Object Tracking
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7. Evaluation of Tracking Performance