ISBN: 9783030611903 - analytic combinatorics for multiple object tracking (15 resultados)

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Hardback. Condición: New. 2021 ed. ?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.…

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.…

Condición: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.

Hardcover. Condición: Brand New. 237 pages. 9.25x6.10x0.79 inches. In Stock.

Hardback. Condición: New. 2021 ed. ?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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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware - 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. 240 pp. Englisch.…

Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents an accessible guide to AC and GF written for engineers to address engineering problemsProvides theory in an easy to understand manner and application of the theory to real life projects and solutionsDescribes GFs and their applicat.…

Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -¿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.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 240 pp. Englisch.…

Condición: New. Print on Demand.

Condición: New. PRINT ON DEMAND.