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Analytic Combinatorics for Multiple ...
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Streit, Roy.
Analytic Combinatorics for Multiple Object Tracking
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Analytic Combinatorics for Multiple Object Tracking/ by Roy Streit, Robert Blair Angle, Murat Efe.
Author:
Streit, Roy.
other author:
Angle, Robert Blair.
Description:
XVI, 221 p. 16 illus., 15 illus. in color.online resource. :
Contained By:
Springer Nature eBook
Subject:
Signal processing. -
Online resource:
https://doi.org/10.1007/978-3-030-61191-0
ISBN:
9783030611910
Analytic Combinatorics for Multiple Object Tracking
Streit, Roy.
Analytic Combinatorics for Multiple Object Tracking
[electronic resource] /by Roy Streit, Robert Blair Angle, Murat Efe. - 1st ed. 2021. - XVI, 221 p. 16 illus., 15 illus. in color.online resource.
Introduction -- Extended object tracking -- Multiple sensors -- Other high computational complexity tracking problems -- Multiframe assignment and combinatorial optimization -- Saddle Point Method -- Multicomplex Algebra -- Automatic Differentiation -- Conclusion.
The book shows that the analytic combinatorics (AC) method encodes the combinatorial problems of multiple object tracking—without information loss—into the derivatives of a generating function (GF). The book lays out an easy-to-follow path from theory to practice and includes salient AC application examples. Since GFs are not widely utilized amongst the tracking community, the book takes the reader from the basics of the subject to applications of theory starting from the simplest problem of single object tracking, and advancing chapter by chapter to more challenging multi-object tracking problems. Many established tracking filters (e.g., Bayes-Markov, PDA, JPDA, IPDA, JIPDA, CPHD, PHD, multi-Bernoulli, MBM, LMBM, and MHT) are derived in this manner with simplicity, economy, and considerable clarity. The AC method gives significant and fresh insights into the modeling assumptions of these filters and, thereby, also shows the potential utility of various approximation methods that are well established techniques in applied mathematics and physics, but are new to tracking. These unexplored possibilities are reviewed in the final chapter of the book. .
ISBN: 9783030611910
Standard No.: 10.1007/978-3-030-61191-0doiSubjects--Topical Terms:
561459
Signal processing.
LC Class. No.: TK5102.9
Dewey Class. No.: 621.382
Analytic Combinatorics for Multiple Object Tracking
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Introduction -- Extended object tracking -- Multiple sensors -- Other high computational complexity tracking problems -- Multiframe assignment and combinatorial optimization -- Saddle Point Method -- Multicomplex Algebra -- Automatic Differentiation -- Conclusion.
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The book shows that the analytic combinatorics (AC) method encodes the combinatorial problems of multiple object tracking—without information loss—into the derivatives of a generating function (GF). The book lays out an easy-to-follow path from theory to practice and includes salient AC application examples. Since GFs are not widely utilized amongst the tracking community, the book takes the reader from the basics of the subject to applications of theory starting from the simplest problem of single object tracking, and advancing chapter by chapter to more challenging multi-object tracking problems. Many established tracking filters (e.g., Bayes-Markov, PDA, JPDA, IPDA, JIPDA, CPHD, PHD, multi-Bernoulli, MBM, LMBM, and MHT) are derived in this manner with simplicity, economy, and considerable clarity. The AC method gives significant and fresh insights into the modeling assumptions of these filters and, thereby, also shows the potential utility of various approximation methods that are well established techniques in applied mathematics and physics, but are new to tracking. These unexplored possibilities are reviewed in the final chapter of the book. .
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