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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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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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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. |
format | Online Article Text |
id | pubmed-9653777 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT hundeandinet multitargetstateandextentestimationforhighresolutionautomotivesensordetections |