Useful Links
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
Multiple Object Tracking
Problem Formulation
Definition of Multiple Targets
Output Requirements
Trajectories
Identities
Tracking-by-Detection Paradigm
Object Detection in Each Frame
Detector Selection and Performance
Detection Confidence Scores
Data Association Across Frames
Cost Matrix Formulation
Distance Metrics
Feature-based Costs
Association Algorithms
Hungarian Algorithm
Optimal Assignment
Computational Complexity
Greedy Assignment
Heuristic Approaches
Trade-offs
Association Cues
Motion Prediction
Predicting Future Positions
Appearance Similarity
Feature Extraction for Re-identification
Spatial Proximity
Overlap-based Association
Common MOT Frameworks
Simple Online and Realtime Tracking
Kalman Filter-based Motion Model
IoU-based Association
DeepSORT
Deep Appearance Descriptor
Enhanced Data Association
Joint Detection and Tracking
End-to-End Learning Approaches
Unified Network Architectures
Joint Loss Functions
Attention and Transformer-based Models
Temporal Attention
Spatial Attention
Sequence-to-sequence Prediction
Previous
3. Single Object Tracking
Go to top
Next
5. Key Challenges in Object Tracking