Challa, Sudha, 1953-
Fundamentals of object tracking / Subhash Challa [and others]. - 1 online resource (xii, 375 pages) : digital, PDF file(s).
Title from publisher's bibliographic system (viewed on 05 Oct 2015).
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.
9780511975837 (ebook)
Linear programming.
Programming (Mathematics)
QA402.5 / .C43 2011
519.7
Fundamentals of object tracking / Subhash Challa [and others]. - 1 online resource (xii, 375 pages) : digital, PDF file(s).
Title from publisher's bibliographic system (viewed on 05 Oct 2015).
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.
9780511975837 (ebook)
Linear programming.
Programming (Mathematics)
QA402.5 / .C43 2011
519.7