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Multi-Target State and Extent Estimation for High Resolution Automotive Sensor Detections

This paper discusses the perception and tracking of individual as well as group targets as applied to multi-lane public traffic. Target tracking problem is formulated as a two hierarchical layer problem—on the first layer, a multi-target tracking problem based on multiple detections is distinguished...

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Detalles Bibliográficos
Autor principal: Hunde, Andinet
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9653777/
https://www.ncbi.nlm.nih.gov/pubmed/36366113
http://dx.doi.org/10.3390/s22218415
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author Hunde, Andinet
author_facet Hunde, Andinet
author_sort Hunde, Andinet
collection PubMed
description This paper discusses the perception and tracking of individual as well as group targets as applied to multi-lane public traffic. Target tracking problem is formulated as a two hierarchical layer problem—on the first layer, a multi-target tracking problem based on multiple detections is distinguished in the measurement space, and on the second (top) layer, group target tracking with birth and death as well as merging and splitting of group target tracks as they evolve in a dynamic scene is represented. This configuration enhances the multi-target tracking performance in situations including but not limited to target initialization(birth), target occlusion, missed detections, unresolved measurement, target maneuver, etc. In addition, group tracking exposes complex individual target interactions to help in situation assessment which is challenging to capture otherwise.
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spelling pubmed-96537772022-11-15 Multi-Target State and Extent Estimation for High Resolution Automotive Sensor Detections Hunde, Andinet Sensors (Basel) Article This paper discusses the perception and tracking of individual as well as group targets as applied to multi-lane public traffic. Target tracking problem is formulated as a two hierarchical layer problem—on the first layer, a multi-target tracking problem based on multiple detections is distinguished in the measurement space, and on the second (top) layer, group target tracking with birth and death as well as merging and splitting of group target tracks as they evolve in a dynamic scene is represented. This configuration enhances the multi-target tracking performance in situations including but not limited to target initialization(birth), target occlusion, missed detections, unresolved measurement, target maneuver, etc. In addition, group tracking exposes complex individual target interactions to help in situation assessment which is challenging to capture otherwise. MDPI 2022-11-02 /pmc/articles/PMC9653777/ /pubmed/36366113 http://dx.doi.org/10.3390/s22218415 Text en © 2022 by the author. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Hunde, Andinet
Multi-Target State and Extent Estimation for High Resolution Automotive Sensor Detections
title Multi-Target State and Extent Estimation for High Resolution Automotive Sensor Detections
title_full Multi-Target State and Extent Estimation for High Resolution Automotive Sensor Detections
title_fullStr Multi-Target State and Extent Estimation for High Resolution Automotive Sensor Detections
title_full_unstemmed Multi-Target State and Extent Estimation for High Resolution Automotive Sensor Detections
title_short Multi-Target State and Extent Estimation for High Resolution Automotive Sensor Detections
title_sort multi-target state and extent estimation for high resolution automotive sensor detections
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9653777/
https://www.ncbi.nlm.nih.gov/pubmed/36366113
http://dx.doi.org/10.3390/s22218415
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