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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
Single Object Tracking
Problem Formulation
Initialization with Ground Truth
Online vs Offline Tracking
Generative Tracking Methods
Template Matching
Cross-correlation
Template Update Strategies
Mean-Shift Tracking
Kernel Density Estimation
Iterative Mode Seeking
Particle Filters
Likelihood Computation
Handling Uncertainty
Discriminative Tracking Methods
Online Learning Classifiers
Adaptive Appearance Models
Update Mechanisms
Correlation Filter-based Trackers
Minimum Output Sum of Squared Error
Filter Training
Filter Application
Kernelized Correlation Filters
Use of Kernel Trick
Multi-channel Features
Discriminative Correlation Filter with Channel and Spatial Reliability
Channel Reliability Estimation
Spatial Reliability Maps
Deep Learning-based SOT
Siamese Network-based Trackers
Fully-Convolutional Siamese Networks
Architecture and Training
Matching Mechanism
Siamese Region Proposal Network
Region Proposal Integration
Multi-scale Tracking
Transformer-based Trackers
Self-attention Mechanisms
Sequence Modeling for Tracking
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2. Fundamental Concepts and Components
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4. Multiple Object Tracking