Tracking multiple objects in terrain

Edward Sobiesk; John A. Hamilton; John A. Marin; Donald E. Brown; Maria Gini

Tracking multiple objects in terrain

Edward Sobiesk, John A. Hamilton, John A. Marin, Donald E. Brown, Maria Gini

Computer Science and Engineering

Research output: Contribution to journal › Conference article › peer-review

1 Scopus citations

Abstract

The digitized battlefield of the 21^st Century will revolutionize the methods used to maintain military command and control. The tremendous amount of data available will necessitate the use of intelligent, automated systems that augment, and in some cases replace, the human structures currently in place. One aspect of such systems is terrain-based tracking. We discuss an intelligent terrain-based system for tracking multiple vehicles moving across terrain. Specifically, our system will extract and utilize knowledge about groups to improve the performance of a discrete state-space motion model. Parallel programming techniques are utilized to efficiently compute probability densities for the vehicles. A learning component will allow for real-time adjustment based on performance.

Original language	English (US)
Pages (from-to)	2842-2847
Number of pages	6
Journal	Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume	3
State	Published - 1998
Event	Proceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics. Part 3 (of 5) - San Diego, CA, USA Duration: Oct 11 1998 → Oct 14 1998

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@article{cd4076435e1745d6ab159b690f27b79c,

title = "Tracking multiple objects in terrain",

abstract = "The digitized battlefield of the 21st Century will revolutionize the methods used to maintain military command and control. The tremendous amount of data available will necessitate the use of intelligent, automated systems that augment, and in some cases replace, the human structures currently in place. One aspect of such systems is terrain-based tracking. We discuss an intelligent terrain-based system for tracking multiple vehicles moving across terrain. Specifically, our system will extract and utilize knowledge about groups to improve the performance of a discrete state-space motion model. Parallel programming techniques are utilized to efficiently compute probability densities for the vehicles. A learning component will allow for real-time adjustment based on performance.",

author = "Edward Sobiesk and Hamilton, {John A.} and Marin, {John A.} and Brown, {Donald E.} and Maria Gini",

year = "1998",

language = "English (US)",

volume = "3",

pages = "2842--2847",

journal = "Proceedings of the IEEE International Conference on Systems, Man and Cybernetics",

issn = "0884-3627",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "Proceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics. Part 3 (of 5) ; Conference date: 11-10-1998 Through 14-10-1998",

}

TY - JOUR

T1 - Tracking multiple objects in terrain

AU - Sobiesk, Edward

AU - Hamilton, John A.

AU - Marin, John A.

AU - Brown, Donald E.

AU - Gini, Maria

PY - 1998

Y1 - 1998

N2 - The digitized battlefield of the 21st Century will revolutionize the methods used to maintain military command and control. The tremendous amount of data available will necessitate the use of intelligent, automated systems that augment, and in some cases replace, the human structures currently in place. One aspect of such systems is terrain-based tracking. We discuss an intelligent terrain-based system for tracking multiple vehicles moving across terrain. Specifically, our system will extract and utilize knowledge about groups to improve the performance of a discrete state-space motion model. Parallel programming techniques are utilized to efficiently compute probability densities for the vehicles. A learning component will allow for real-time adjustment based on performance.

AB - The digitized battlefield of the 21st Century will revolutionize the methods used to maintain military command and control. The tremendous amount of data available will necessitate the use of intelligent, automated systems that augment, and in some cases replace, the human structures currently in place. One aspect of such systems is terrain-based tracking. We discuss an intelligent terrain-based system for tracking multiple vehicles moving across terrain. Specifically, our system will extract and utilize knowledge about groups to improve the performance of a discrete state-space motion model. Parallel programming techniques are utilized to efficiently compute probability densities for the vehicles. A learning component will allow for real-time adjustment based on performance.

UR - http://www.scopus.com/inward/record.url?scp=0032310769&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0032310769&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:0032310769

SN - 0884-3627

VL - 3

SP - 2842

EP - 2847

JO - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

JF - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

T2 - Proceedings of the 1998 IEEE International Conference on Systems, Man, and Cybernetics. Part 3 (of 5)

Y2 - 11 October 1998 through 14 October 1998

ER -

Tracking multiple objects in terrain

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