Analytic Combinatorics for Multiple Object TrackingКНИГИ » НАУКА И УЧЕБА
[img=left]https://cv02.twirpx.net/3297/3297702.jpg?t=20201128154600[/img] Название: Analytic Combinatorics for Multiple Object Tracking Автор: Streit R.L., Angle R.B., Efe M. Издательство: Springer Год: 2021 Формат: PDF Страниц: 228 Для сайта:Mirknig.su Размер: 3,82 МБ Язык: английский
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. Introduction to Analytic Combinatorics and Tracking Tracking One Object Tracking a Specified Number of Objects Tracking a Variable Number of Objects Multi-Bernoulli Mixture and Multiple Hypothesis Tracking Filters Wither Now and Why
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Analytic Combinatorics for Multiple Object Tracking 
