國立高雄大學圖資館 |

Language: English

Back

Track-before-detect using expectatio...

Davey, Samuel J.

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

Record Type:	Electronic resources : Monograph/item
Title/Author:	Track-before-detect using expectation maximisationby 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.
Contained By:	Springer eBooks
Subject:	Gaussian measures.
Online resource:	http://dx.doi.org/10.1007/978-981-10-7593-3
ISBN:	9789811075933$q(electronic bk.)

Track-before-detect using expectation maximisationthe 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$q(electronic bk.)

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

777157
Gaussian measures.

LC Class. No.: QA312

Dewey Class. No.: 519.23

Track-before-detect using expectation maximisationthe histogram probabilistic multi-hypothesis tracker: theory and applications /
LDR:02302nmm a2200349 a 4500 001 531874
003 DE-He213
005 20180208173101.0
006 m d
007 cr nn 008maaau
008 181113s2018 si s 0 eng d
020 $a 9789811075933$q(electronic bk.)
020 $a 9789811075926$q(paper)
024 7 $a 10.1007/978-981-10-7593-3 $2 doi
035 $a 978-981-10-7593-3
040 $a GP $c GP
041 0 $a eng
050 4 $a QA312
072 7 $a TTBM $2 bicssc
072 7 $a UYS $2 bicssc
072 7 $a TEC008000 $2 bisacsh
072 7 $a COM073000 $2 bisacsh
082 0 4 $a 519.23 $2 23
090 $a QA312 $b .D248 2018
100 1 $a Davey, Samuel J. $3 806551
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.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2018.
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.
650 0 $a Gaussian measures. $3 777157
650 1 4 $a Engineering. $3 210888
650 2 4 $a Signal, Image and Speech Processing. $3 273768
650 2 4 $a Image Processing and Computer Vision. $3 274051
650 2 4 $a Computational Science and Engineering. $3 274685
650 2 4 $a Computational Intelligence. $3 338479
700 1 $a Gaetjens, Han X. $3 806552
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Signals and communication technology. $3 557664
856 4 0 $u http://dx.doi.org/10.1007/978-981-10-7593-3
950 $a Engineering (Springer-11647)