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Higher-Order Multiple Object Tracking / Titelei/Inhaltsverzeichnis
Higher-Order Multiple Object Tracking / Titelei/Inhaltsverzeichnis
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I–XVIII
Titelei/Inhaltsverzeichnis
I–XVIII
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1–32
1 Introduction
1–32
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1.1 Applications
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1.2 The Multiple Object Tracking Problem
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1.2.1 Video-based Multiple Object Tracking (MOT)
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1.2.2 Tracking-by-detection
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1.3 Challenges of Multiple Object Tracking
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1.3.1 Errors caused by the object detector
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1.3.2 Challenges in discriminative features
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1.3.3 Combinatorial challenges
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1.4 Related Work
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1.5 Contributions
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1.6 List of Publications
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1.7 Outline
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33–79
2 Fundamentals
33–79
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2.1 Sets, Maps, and Matrices
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2.2 Probability Theory
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2.3 Graph Theory
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2.3.1 Important graph classes
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2.3.2 Computations on graphs
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2.4 Machine Learning
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2.4.1 Supervised learning
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2.4.2 Logistic regression
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2.4.3 Neural networks
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2.5 Computational Complexity Theory
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2.6 Optimization Theory
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2.6.1 Linear programming
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2.6.2 Binary linear programming
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2.6.3 Quadratic programming
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2.6.4 Binary quadratic programming
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2.6.5 Non-linear optimization
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2.7 Multi-Object Tracking
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2.7.1 Object detectors
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2.7.2 Appearance features
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2.7.3 Datasets
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2.7.4 MOT metrics
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80–129
3 HO-MOT with Signal Fusion
80–129
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3.1 Introduction
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3.2 Signal Fusion as Weighted Graph Labeling Problem
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3.2.1 Related work
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3.2.2 Data association model for signal fusion
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3.3 Frank-Wolfe Optimizer for Weighted Graph Labeling Problems
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3.3.1 Related work
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3.3.2 Frank-Wolfe Optimizer for Binary Solutions
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3.4 Multiple People Tracking by Fusing Head and People Detections
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3.4.1 Data association model
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3.4.2 Experimental results
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3.5 Simultaneous Identification and Tracking of Multiple People using Video and IMUs
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3.5.1 Related work
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3.5.2 Method
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3.5.3 Evaluation
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3.6 Conclusion
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130–164
4 Lifted Disjoint Paths
130–164
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4.1 Introduction
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4.2 Related Work
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4.3 Problem Formulation
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4.4 Constraints
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4.5 Separation
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4.6 Complexity
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4.7 Experiments
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4.7.1 Graph construction
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4.7.2 Pre-processing and post-processing
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4.7.3 Cost learning
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4.7.4 Implementation details on the lifted disjoint paths solver
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4.7.5 Experiment setup
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4.7.6 Benefit of long-range edges
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4.7.7 Ablation study on post-processing methods
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4.7.8 Accuracy of the fusion network
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4.7.9 Qualitative evaluations
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4.7.10 Benchmark evaluations
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4.8 Conclusion
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165–171
5 Conclusions
165–171
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172–196
Bibliography
172–196
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Higher-Order Multiple Object Tracking , page I - XVIII
Titelei/Inhaltsverzeichnis
Autoren
Roberto D. Henschel
DOI
doi.org/10.51202/9783186875105-I
ISBN print: 978-3-18-387510-8
ISBN online: 978-3-18-687510-5
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