Fundamentals of Object Tracking

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9780521876285: Fundamentals of Object Tracking

Kalman filter, particle filter, IMM, PDA, ITS, random sets... The number of useful object-tracking methods is exploding. But how are they related? How do they help track everything from aircraft, missiles and extra-terrestrial objects to people and lymphocyte cells? How can they be adapted to novel applications? Fundamentals of Object Tracking tells you how. Starting with the generic object-tracking problem, it outlines the generic Bayesian solution. It then shows systematically how to formulate the major tracking problems - maneuvering, multiobject, clutter, out-of-sequence sensors - within this Bayesian framework and how to derive the standard tracking solutions. This structured approach makes very complex object-tracking algorithms accessible to the growing number of users working on real-world tracking problems and supports them in designing their own tracking filters under their unique application constraints. The book concludes with a chapter on issues critical to successful implementation of tracking algorithms, such as track initialization and merging.

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Book Description:

In recent years there have been major advances in the use of object tracking technology for both military and civilian applications. This book provides a solid foundation to this field and its methods for the growing number of students, engineers and researchers working on real-world tracking problems.

About the Author:

Subhash Challa is a Senior Principal Research Scientist at NICTA (National ICT Australia) VRL at the University of Melbourne (UoM). He is also one of the co-founders of SenSen Networks Pty Ltd and has been the Director and CTO of the company.

Mark R. Morelande is a Senior Research Fellow in the Melbourne Systems Laboratory at the University of Melbourne.

Darko Mušicki is a Professor in the Department of Electronic Systems Engineering at Hanyang University in Ansan, Republic of Korea.

Robin J. Evans is a Professor of Electrical Engineering and Director of the Victoria Research Laboratory at the University of Melbourne.

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Subhash Challa, Robin J. Evans, Mark R. Morelande
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Book Description CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2011. Hardback. Book Condition: New. Language: English . Brand New Book. Kalman filter, particle filter, IMM, PDA, ITS, random sets.The number of useful object-tracking methods is exploding. But how are they related? How do they help track everything from aircraft, missiles and extra-terrestrial objects to people and lymphocyte cells? How can they be adapted to novel applications? Fundamentals of Object Tracking tells you how. Starting with the generic object-tracking problem, it outlines the generic Bayesian solution. It then shows systematically how to formulate the major tracking problems - maneuvering, multiobject, clutter, out-of-sequence sensors - within this Bayesian framework and how to derive the standard tracking solutions. This structured approach makes very complex object-tracking algorithms accessible to the growing number of users working on real-world tracking problems and supports them in designing their own tracking filters under their unique application constraints. The book concludes with a chapter on issues critical to successful implementation of tracking algorithms, such as track initialization and merging. Bookseller Inventory # AAA9780521876285

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Book Description CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2011. Hardback. Book Condition: New. Language: English . Brand New Book. Kalman filter, particle filter, IMM, PDA, ITS, random sets.The number of useful object-tracking methods is exploding. But how are they related? How do they help track everything from aircraft, missiles and extra-terrestrial objects to people and lymphocyte cells? How can they be adapted to novel applications? Fundamentals of Object Tracking tells you how. Starting with the generic object-tracking problem, it outlines the generic Bayesian solution. It then shows systematically how to formulate the major tracking problems - maneuvering, multiobject, clutter, out-of-sequence sensors - within this Bayesian framework and how to derive the standard tracking solutions. This structured approach makes very complex object-tracking algorithms accessible to the growing number of users working on real-world tracking problems and supports them in designing their own tracking filters under their unique application constraints. The book concludes with a chapter on issues critical to successful implementation of tracking algorithms, such as track initialization and merging. Bookseller Inventory # AAA9780521876285

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