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Fundamentals of Object Tracking

£67.00

  • Date Published: July 2011
  • availability: In stock
  • format: Hardback
  • isbn: 9780521876285
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  • 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.

    • A unified Bayesian approach to object tracking, which makes the techniques more accessible to non-specialists
    • Presents the performance bounds of algorithms for each of the real-world scenarios studied in the book
    • Includes illustrative examples to encourage rapid adoption and adaptation of object tracking techniques
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    Customer reviews

    23rd Jun 2014 by CUPEditorial

    Erratum from customer: On page 10 there is a series of six graphs with three curves displayed in each. Under the image it says: "Figure 1.6 Prior p(x) (grey line), likelihood L(x) = p(y|x) (black line) and posterior p(x|y) (grey line) for data...". I believe that the prior p(x) is actually shown on the graph as a dotted line so this should really read: "Figure 1.6 Prior p(x) (dotted line), likelihood L(x) = p(y|x) (black line) and posterior p(x|y) (grey line) for data...".

    Review was not posted due to profanity

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    Product details

    • Date Published: July 2011
    • format: Hardback
    • isbn: 9780521876285
    • length: 392 pages
    • dimensions: 255 x 181 x 28 mm
    • weight: 0.91kg
    • contains: 60 b/w illus. 1 colour illus.
    • availability: In stock
  • Table of Contents

    Preface
    1. Introduction to object tracking
    2. Filtering theory and non-maneuvering object tracking
    3. Maneuvering object tracking
    4. Single-object tracking in clutter
    5. Single- and multiple-object tracking in clutter: object-existence-based approach
    6. Multiple-object tracking in clutter: random-set-based approach
    7. Bayesian smoothing algorithms for object tracking
    8. Object tracking with time-delayed, out-of-sequence measurements
    9. Practical object tracking
    A. Mathematical and statistical preliminaries
    B. Finite set statistics (FISST)
    C. Pseudo-functions in object tracking
    References
    Index.

  • Authors

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

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

    Robin J. Evans, University of Melbourne
    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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