Optimization of lateral interaction in accumulative computation on GPU-based platform

The lateral interaction in accumulative computation (LIAC) algorithm is a biologically inspired method that allows us to detect moving objects from image sequences acquired from fixed surveillance cameras. This method achieves excellent precision but requires a high processing time. Sequential imple...

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Detalhes bibliográficos
Autores: Bermúdez Marín, Aurelio, Montero Simarro, Francisco, López Bonal, María Teresa, Fernández Caballero, Antonio, Sánchez García, José Luis
Tipo de documento: artigo
Data de publicação:2019
País:España
Recursos:Universidad de Castilla-La Mancha
Repositório:RUIdeRA. Repositorio Institucional de la UCLM
OAI Identifier:oai:ruidera.uclm.es:10578/32909
Acesso em linha:https://doi.org/10.1007/s11227-018-02736-y
https://hdl.handle.net/10578/32909
Access Level:Acceso aberto
Palavra-chave:Acceleration
GPU
HPC
Lateral interaction in accumulative computation
Motion detection
Optimization
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spelling Optimization of lateral interaction in accumulative computation on GPU-based platformBermúdez Marín, AurelioMontero Simarro, FranciscoLópez Bonal, María TeresaFernández Caballero, AntonioSánchez García, José LuisAccelerationGPUHPCLateral interaction in accumulative computationMotion detectionOptimizationThe lateral interaction in accumulative computation (LIAC) algorithm is a biologically inspired method that allows us to detect moving objects from image sequences acquired from fixed surveillance cameras. This method achieves excellent precision but requires a high processing time. Sequential implementation is too slow and cannot achieve real-time processing. In this paper, we present several improvements to the LIAC algorithm that increase its efficiency in terms of execution time and energy consumption. In particular, a GPU-based implementation delivers the same precision and is notably faster and more energy efficient than the sequential implementation.Springer202420242019info:eu-repo/semantics/articleapplication/pdfapplication/pdfhttps://doi.org/10.1007/s11227-018-02736-yhttps://hdl.handle.net/10578/32909reponame:RUIdeRA. Repositorio Institucional de la UCLMinstname:Universidad de Castilla-La ManchaInglésDPI2016-80894-RTIN2015-66972-C5-2-Rinfo:eu-repo/semantics/openAccessoai:ruidera.uclm.es:10578/329092026-05-27T07:36:41Z
dc.title.none.fl_str_mv Optimization of lateral interaction in accumulative computation on GPU-based platform
title Optimization of lateral interaction in accumulative computation on GPU-based platform
spellingShingle Optimization of lateral interaction in accumulative computation on GPU-based platform
Bermúdez Marín, Aurelio
Acceleration
GPU
HPC
Lateral interaction in accumulative computation
Motion detection
Optimization
title_short Optimization of lateral interaction in accumulative computation on GPU-based platform
title_full Optimization of lateral interaction in accumulative computation on GPU-based platform
title_fullStr Optimization of lateral interaction in accumulative computation on GPU-based platform
title_full_unstemmed Optimization of lateral interaction in accumulative computation on GPU-based platform
title_sort Optimization of lateral interaction in accumulative computation on GPU-based platform
dc.creator.none.fl_str_mv Bermúdez Marín, Aurelio
Montero Simarro, Francisco
López Bonal, María Teresa
Fernández Caballero, Antonio
Sánchez García, José Luis
author Bermúdez Marín, Aurelio
author_facet Bermúdez Marín, Aurelio
Montero Simarro, Francisco
López Bonal, María Teresa
Fernández Caballero, Antonio
Sánchez García, José Luis
author_role author
author2 Montero Simarro, Francisco
López Bonal, María Teresa
Fernández Caballero, Antonio
Sánchez García, José Luis
author2_role author
author
author
author
dc.subject.none.fl_str_mv Acceleration
GPU
HPC
Lateral interaction in accumulative computation
Motion detection
Optimization
topic Acceleration
GPU
HPC
Lateral interaction in accumulative computation
Motion detection
Optimization
description The lateral interaction in accumulative computation (LIAC) algorithm is a biologically inspired method that allows us to detect moving objects from image sequences acquired from fixed surveillance cameras. This method achieves excellent precision but requires a high processing time. Sequential implementation is too slow and cannot achieve real-time processing. In this paper, we present several improvements to the LIAC algorithm that increase its efficiency in terms of execution time and energy consumption. In particular, a GPU-based implementation delivers the same precision and is notably faster and more energy efficient than the sequential implementation.
publishDate 2019
dc.date.none.fl_str_mv 2019
2024
2024
dc.type.none.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://doi.org/10.1007/s11227-018-02736-y
https://hdl.handle.net/10578/32909
url https://doi.org/10.1007/s11227-018-02736-y
https://hdl.handle.net/10578/32909
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv DPI2016-80894-R
TIN2015-66972-C5-2-R
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:RUIdeRA. Repositorio Institucional de la UCLM
instname:Universidad de Castilla-La Mancha
instname_str Universidad de Castilla-La Mancha
reponame_str RUIdeRA. Repositorio Institucional de la UCLM
collection RUIdeRA. Repositorio Institucional de la UCLM
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,300719

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