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A Low Cost Matching Motion Estimation Sensor Based on the NIOS II Microprocessor

This work presents the implementation of a matching-based motion estimation sensor on a Field Programmable Gate Array (FPGA) and NIOS II microprocessor applying a C to Hardware (C2H) acceleration paradigm. The design, which involves several matching algorithms, is mapped using Very Large Scale Integ...

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Detalles Bibliográficos
Autores principales: González, Diego, Botella, Guillermo, Meyer-Baese, Uwe, García, Carlos, Sanz, Concepción, Prieto-Matías, Manuel, Tirado, Francisco
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Molecular Diversity Preservation International (MDPI) 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3545560/
https://www.ncbi.nlm.nih.gov/pubmed/23201989
http://dx.doi.org/10.3390/s121013126
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author González, Diego
Botella, Guillermo
Meyer-Baese, Uwe
García, Carlos
Sanz, Concepción
Prieto-Matías, Manuel
Tirado, Francisco
author_facet González, Diego
Botella, Guillermo
Meyer-Baese, Uwe
García, Carlos
Sanz, Concepción
Prieto-Matías, Manuel
Tirado, Francisco
author_sort González, Diego
collection PubMed
description This work presents the implementation of a matching-based motion estimation sensor on a Field Programmable Gate Array (FPGA) and NIOS II microprocessor applying a C to Hardware (C2H) acceleration paradigm. The design, which involves several matching algorithms, is mapped using Very Large Scale Integration (VLSI) technology. These algorithms, as well as the hardware implementation, are presented here together with an extensive analysis of the resources needed and the throughput obtained. The developed low-cost system is practical for real-time throughput and reduced power consumption and is useful in robotic applications, such as tracking, navigation using an unmanned vehicle, or as part of a more complex system.
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spelling pubmed-35455602013-01-23 A Low Cost Matching Motion Estimation Sensor Based on the NIOS II Microprocessor González, Diego Botella, Guillermo Meyer-Baese, Uwe García, Carlos Sanz, Concepción Prieto-Matías, Manuel Tirado, Francisco Sensors (Basel) Article This work presents the implementation of a matching-based motion estimation sensor on a Field Programmable Gate Array (FPGA) and NIOS II microprocessor applying a C to Hardware (C2H) acceleration paradigm. The design, which involves several matching algorithms, is mapped using Very Large Scale Integration (VLSI) technology. These algorithms, as well as the hardware implementation, are presented here together with an extensive analysis of the resources needed and the throughput obtained. The developed low-cost system is practical for real-time throughput and reduced power consumption and is useful in robotic applications, such as tracking, navigation using an unmanned vehicle, or as part of a more complex system. Molecular Diversity Preservation International (MDPI) 2012-09-27 /pmc/articles/PMC3545560/ /pubmed/23201989 http://dx.doi.org/10.3390/s121013126 Text en © 2012 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 license (http://creativecommons.org/licenses/by/3.0/).
spellingShingle Article
González, Diego
Botella, Guillermo
Meyer-Baese, Uwe
García, Carlos
Sanz, Concepción
Prieto-Matías, Manuel
Tirado, Francisco
A Low Cost Matching Motion Estimation Sensor Based on the NIOS II Microprocessor
title A Low Cost Matching Motion Estimation Sensor Based on the NIOS II Microprocessor
title_full A Low Cost Matching Motion Estimation Sensor Based on the NIOS II Microprocessor
title_fullStr A Low Cost Matching Motion Estimation Sensor Based on the NIOS II Microprocessor
title_full_unstemmed A Low Cost Matching Motion Estimation Sensor Based on the NIOS II Microprocessor
title_short A Low Cost Matching Motion Estimation Sensor Based on the NIOS II Microprocessor
title_sort low cost matching motion estimation sensor based on the nios ii microprocessor
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3545560/
https://www.ncbi.nlm.nih.gov/pubmed/23201989
http://dx.doi.org/10.3390/s121013126
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