This title deals with the creation of the algorithm backbone that enables a computer to perceive humans in a monitored space, by processing the signals that humans use in order to perform a task.
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| Preface | |
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| Acknowledgments | |
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| List of Figures | |
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| List of Tables | |
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| Introduction | |
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| Person tracking | |
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| Why person tracking? | |
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| Person tracking challenges | |
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| Book organisation | |
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| Tracking Algorithms | |
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| Introduction | |
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| Tracking | |
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| Deterministic tracking | |
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| Stochastic trackers | |
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| Recursive Bayesian filtering | |
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| Kalman filter | |
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| Particle filter | |
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| Particle filter trackers | |
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| Object models | |
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| Object model for proposal distribution | |
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| Degeneracy of SIS particle filter | |
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| Optimum proposal distributions | |
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| Resampling | |
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| Sequential Importance Resampling particle filter | |
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| Conclusions | |
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| Audio Tracking | |
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| Introduction | |
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| Multiple audio sensors | |
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| System model | |
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| The image model | |
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| Microphone arrays and then geometries | |
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| Audio trackers | |
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| Linear intersection | |
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| Particle filtering | |
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| Multiple speakers | |
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| Detection in audio | |
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| Time delay estimation | |
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| Beamforming | |
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| Voice activity detection | |
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| System parameters | |
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| Performance measures | |
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| Simulations | |
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| Visual Tracking | |
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| Introduction | |
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| From 3D world to 2D images | |
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| 3D imaging | |
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| Measurements in images | |
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| Colour matching | |
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| Colour without spatial information | |
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| Colour with spatial information | |
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| Outline matching | |
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| Clutter attenuation by edge orientation | |
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| View changes handling by modelling in 3D | |
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| Moving objects | |
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| Frame-by-frame difference | |
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| Adaptive background estimation | |
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| Motion likelihood | |
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| Face detection | |
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| Viola-Jones face detector | |
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| Face validation | |
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| Face likelihood | |
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| Visual tracking systems | |
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| Deterministic tracking | |
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| Template matching | |
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| Mean-Shift | |
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| Stochastic tracking | |
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| Kalman filter | |
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| Colour-based particle filter face tracker | |
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| Measurement-assisted proposal distribution | |
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| Particle filter face tracker with colour-assisted proposal distribution | |
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| Particle filter face tracker using face likelihood | |
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| Conclusions | |
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| Multimodal Tracking | |
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| Introduction | |
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| Likelihood combination | |
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| Multiplying face and colour likelihoods | |
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| Tracker output combination | |
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| Deterministic fusion of independent trackers | |
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| Kalman fusion of independent audio and visual trackers | |
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| Partitioned sampling | |
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| Joint multi-cue face tracker employing partitioned sampling | |
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| Joint audio and visual tracker employing partitioned sampling | |
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| Sensor synchronisation | |
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| Conclusions | |
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| Applications | |
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| Smart Spaces | |
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| The Smart Home | |
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| The Smart Office | |
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| Video-conferencing | |
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| Entertainment | |
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| Personalised media broadcasting | |
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| Security and surveillance | |
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| Robotics | |
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| Marketing and retail | |
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| Conclusions | |
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| Bibliography | |
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| Index | |
