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Track-before-detect using expectatio...

Davey, Samuel J.

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Track-before-detect using expectation maximisation = the histogram probabilistic multi-hypothesis tracker: theory and applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Track-before-detect using expectation maximisation/ by Samuel J. Davey, Han X. Gaetjens.
Reminder of title:	the histogram probabilistic multi-hypothesis tracker: theory and applications /
Author:	Davey, Samuel J.
other author:	Gaetjens, Han X.
Published:	Singapore :Springer Singapore : : 2018.,
Description:	xxi, 352 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Foreword -- Introduction -- Idealised Track-Before-Detect -- Point Measurement Probabilistic Multi-Hypothesis Tracking -- Histogram ProbabilisticMulti-Hypothesis Tracking -- Implementation Considerations -- Poisson Scattering Field -- Non-linear Non-Gaussian Targets -- Adaptive Appearance Models -- H-PMHT with Attribute Data -- Radar and Sonar Track-Before-Detect -- Tracking in Full Motion Video -- Related Methods -- Summary and Prognostications.
Contained By:	Springer eBooks
Subject:	Gaussian measures. -
Online resource:	http://dx.doi.org/10.1007/978-981-10-7593-3
ISBN:	9789811075933

Track-before-detect using expectation maximisation = the histogram probabilistic multi-hypothesis tracker: theory and applications /
Davey, Samuel J.

Track-before-detect using expectation maximisationthe histogram probabilistic multi-hypothesis tracker: theory and applications /[electronic resource] :by Samuel J. Davey, Han X. Gaetjens. - Singapore :Springer Singapore :2018. - xxi, 352 p. :ill. (some col.), digital ;24 cm. - Signals and communication technology,1860-4862. - Signals and communication technology..

Foreword -- Introduction -- Idealised Track-Before-Detect -- Point Measurement Probabilistic Multi-Hypothesis Tracking -- Histogram ProbabilisticMulti-Hypothesis Tracking -- Implementation Considerations -- Poisson Scattering Field -- Non-linear Non-Gaussian Targets -- Adaptive Appearance Models -- H-PMHT with Attribute Data -- Radar and Sonar Track-Before-Detect -- Tracking in Full Motion Video -- Related Methods -- Summary and Prognostications.

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.

ISBN: 9789811075933

Standard No.: 10.1007/978-981-10-7593-3doiSubjects--Topical Terms:

672950
Gaussian measures.

LC Class. No.: QA312

Dewey Class. No.: 519.23

Track-before-detect using expectation maximisation = the histogram probabilistic multi-hypothesis tracker: theory and applications /
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245 1 0 $a Track-before-detect using expectation maximisation $h [electronic resource] : $b the histogram probabilistic multi-hypothesis tracker: theory and applications / $c by Samuel J. Davey, Han X. Gaetjens.
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300 $a xxi, 352 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Signals and communication technology, $x 1860-4862
505 0 $a Foreword -- Introduction -- Idealised Track-Before-Detect -- Point Measurement Probabilistic Multi-Hypothesis Tracking -- Histogram ProbabilisticMulti-Hypothesis Tracking -- Implementation Considerations -- Poisson Scattering Field -- Non-linear Non-Gaussian Targets -- Adaptive Appearance Models -- H-PMHT with Attribute Data -- Radar and Sonar Track-Before-Detect -- Tracking in Full Motion Video -- Related Methods -- Summary and Prognostications.
520 $a 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.
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