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Recent Advances in Stochastic Sensor Control for Multi-Object Tracking
In many multi-object tracking applications, the sensor(s) may have controllable states. Examples include movable sensors in multi-target tracking applications in defence, and unmanned air vehicles (UAVs) as sensors in multi-object systems used in civil applications such as inspection and fault detec...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6749220/ https://www.ncbi.nlm.nih.gov/pubmed/31480502 http://dx.doi.org/10.3390/s19173790 |
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author | Panicker, Sabita Gostar, Amirali Khodadadian Bab-Hadiashar, Alireza Hoseinnezhad, Reza |
author_facet | Panicker, Sabita Gostar, Amirali Khodadadian Bab-Hadiashar, Alireza Hoseinnezhad, Reza |
author_sort | Panicker, Sabita |
collection | PubMed |
description | In many multi-object tracking applications, the sensor(s) may have controllable states. Examples include movable sensors in multi-target tracking applications in defence, and unmanned air vehicles (UAVs) as sensors in multi-object systems used in civil applications such as inspection and fault detection. Uncertainties in the number of objects (due to random appearances and disappearances) as well as false alarms and detection uncertainties collectively make the above problem a highly challenging stochastic sensor control problem. Numerous solutions have been proposed to tackle the problem of precise control of sensor(s) for multi-object detection and tracking, and, in this work, recent contributions towards the advancement in the domain are comprehensively reviewed. After an introduction, we provide an overview of the sensor control problem and present the key components of sensor control solutions in general. Then, we present a categorization of the existing methods and review those methods under each category. The categorization includes a new generation of solutions called selective sensor control that have been recently developed for applications where particular objects of interest need to be accurately detected and tracked by controllable sensors. |
format | Online Article Text |
id | pubmed-6749220 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-67492202019-09-27 Recent Advances in Stochastic Sensor Control for Multi-Object Tracking Panicker, Sabita Gostar, Amirali Khodadadian Bab-Hadiashar, Alireza Hoseinnezhad, Reza Sensors (Basel) Review In many multi-object tracking applications, the sensor(s) may have controllable states. Examples include movable sensors in multi-target tracking applications in defence, and unmanned air vehicles (UAVs) as sensors in multi-object systems used in civil applications such as inspection and fault detection. Uncertainties in the number of objects (due to random appearances and disappearances) as well as false alarms and detection uncertainties collectively make the above problem a highly challenging stochastic sensor control problem. Numerous solutions have been proposed to tackle the problem of precise control of sensor(s) for multi-object detection and tracking, and, in this work, recent contributions towards the advancement in the domain are comprehensively reviewed. After an introduction, we provide an overview of the sensor control problem and present the key components of sensor control solutions in general. Then, we present a categorization of the existing methods and review those methods under each category. The categorization includes a new generation of solutions called selective sensor control that have been recently developed for applications where particular objects of interest need to be accurately detected and tracked by controllable sensors. MDPI 2019-09-01 /pmc/articles/PMC6749220/ /pubmed/31480502 http://dx.doi.org/10.3390/s19173790 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Panicker, Sabita Gostar, Amirali Khodadadian Bab-Hadiashar, Alireza Hoseinnezhad, Reza Recent Advances in Stochastic Sensor Control for Multi-Object Tracking |
title | Recent Advances in Stochastic Sensor Control for Multi-Object Tracking |
title_full | Recent Advances in Stochastic Sensor Control for Multi-Object Tracking |
title_fullStr | Recent Advances in Stochastic Sensor Control for Multi-Object Tracking |
title_full_unstemmed | Recent Advances in Stochastic Sensor Control for Multi-Object Tracking |
title_short | Recent Advances in Stochastic Sensor Control for Multi-Object Tracking |
title_sort | recent advances in stochastic sensor control for multi-object tracking |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6749220/ https://www.ncbi.nlm.nih.gov/pubmed/31480502 http://dx.doi.org/10.3390/s19173790 |
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