Track-Before-Detect Using Expectation Maximisation The Histogram Probabilistic Multi-hypothesis Tracker: Theory and Applications /

This book offers a detailed description of the histogram probabilistic multi-hypothesis tracker (H-PMHT), providing an accessible and intuitive introduction to the mathematical mechanics of H-PMHT as well as a definitive reference source for the existing literature on the method. Beginning with basi...

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Bibliographic Details
Main Authors: Davey, Samuel J. (Author), Gaetjens, Han X. (Author)
Corporate Author: SpringerLink (Online service)
Format: e-Book
Language:English
Published: Singapore : Springer Nature Singapore : Imprint: Springer, 2018.
Edition:1st ed. 2018.
Series:Signals and Communication Technology,
Subjects:
Signal processing.
Computer vision.
Mathematics > Data processing.
Computational intelligence.
Signal, Speech and Image Processing.
Computer Vision.
Computational Science and Engineering.
Computational Intelligence.
Online Access:Full-text access
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Description
Summary:This book offers a detailed description of the histogram probabilistic multi-hypothesis tracker (H-PMHT), providing an accessible and intuitive introduction to the mathematical mechanics of H-PMHT as well as a definitive reference source for the existing literature on the method. Beginning with basic concepts, the authors then move on to address extensions of the method to a broad class of tracking problems. The latter chapters present applications using recorded data from experimental radar, sonar and video sensor systems. The book is supplemented with software that both furthers readers' understanding and acts as a toolkit for those who wish to apply the methods to their own problems.
Physical Description:XXI, 352 p. 127 illus., 117 illus. in color. online resource.
ISBN:9789811075933
ISSN:1860-4870
DOI:10.1007/978-981-10-7593-3

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