Video Tracking

Foreword.
About the authors.
Preface.
Acknowledgments.
Notations.
Acronyms.
1 What is video tracking?
1.1 Introduction.
1.2 The design of a video tracker.
1.3 Problem formulation.
1.4 Interactive versus automated tracking.
1.5 Summary.
2 Applications.
2.1 Introduction.
2.2 Media production and augmented reality.
2.3 Medical applications and biological research.
2.4 Surveillance and business intelligence.
2.5 Robotics and unmanned vehicles.
2.6 Tele-collaboration and interactive gaming.
2.7 Art installations and performances.
2.8 Summary.
References.
3 Feature extraction.
3.1 Introduction.
3.2 From light to useful information.
3.3 Low-level features.
3.4 Mid-level features.
3.5 High-level features.
3.6 Summary.
References.
4 Target representation.
4.1 Introduction.
4.2 Shape representation.
4.3 Appearance representation.
4.4 Summary.
References
5 Localisation.
5.1 Introduction.
5.2 Single-hypothesis methods.
5.3 Multi-hypothesis methods.
5.4 Summary.
References.
6 Fusion.
6.1 Introduction.
6.2 Fusion strategies.
6.3 Feature fusion in a Particle Filter.
6.4 Summary.
References.
7 Multi-target management.
7.1 Introduction.
7.2 Measurement validation.
7.3 Data association.
7.4 Random Finite Sets for tracking.
7.5 Probabilistic Hypothesis Density filter.
7.6 The Particle PHD filter.
7.7 Summary.
References.
8 Context modeling.
8.1 Introduction.
8.2 Tracking with context modelling.
8.3 Birth and clutter intensity estimation.
8.4 Summary.
References.
9 Performance evaluation.
9.1 Introduction.
9.2 Analytical vs. empirical methods.
9.3 Ground truth.
9.4 Evaluation scores.
9.5 Comparing trackers.
9.6 Evaluation protocols.
9.7 Datasets.
9.8 Summary.
References.
Epilogue.
Further reading.
Appendix A: Comparative results.
A.1 Single versus structural histogram.
A.1.1 Experimental setup.
A.1.2 Discussion.
A.2 Localisation algorithms.
A.2.1 Experimental setup.
A.2.2 Discussion.
A.3 Multi-feature fusion.
A.3.1 Experimental setup.
A.3.2 Reliability scores.
A.3.3 Adaptive versus non-adaptive tracker.
A.3.4 Computational complexity.
A.4 PHD filter.
A.4.1 Experimental setup.
A.4.2 Discussion.
A.4.3 Failure modalities.
A.4.4 Computational cost.
A.5 Context modelling.
A.5.1 Experimental setup.
A.5.2 Discussion.
References.
Index.