Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/114802
Campo DC | Valor | idioma |
---|---|---|
dc.contributor.author | Ortega Zamorano, Francisco | en_US |
dc.contributor.author | Molina-Cabello, Miguel A. | en_US |
dc.contributor.author | López-Rubio, Ezequiel | en_US |
dc.contributor.author | Palomo, Esteban J. | en_US |
dc.date.accessioned | 2022-05-18T14:31:06Z | - |
dc.date.available | 2022-05-18T14:31:06Z | - |
dc.date.issued | 2016 | en_US |
dc.identifier.issn | 0957-4174 | en_US |
dc.identifier.uri | http://hdl.handle.net/10553/114802 | - |
dc.description.abstract | Most current approaches to computer vision are based on expensive, high performance hardware to meet the heavy computational requirements of the employed algorithms. These system architectures are severely limited in their practical application due to financial and technical limitations. In this work a different strategy is used, namely the development of an inexpensive and easy to deploy computer vision system for motion detection. This is achieved by three means. First of all, an affordable and flexible hardware platform is employed. Secondly, the motion detection algorithm is specifically tailored to involve a very small computational load. Thirdly, a fixed point programming paradigm is followed in implementing the system so as to further reduce the computational requirements. The proposed system is experimentally compared to the standard motion detector for a wide range of benchmark videos. The reported results indicate that our proposal attains substantially better performance, while it remains affordable and easy to install in practice. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | Expert Systems with Applications | en_US |
dc.source | Expert Systems with Applications [ISSN 0957-4174], v. 64, p. 476-489 | en_US |
dc.subject | 1203 Ciencia de los ordenadores | en_US |
dc.subject.other | Self-organizing map | en_US |
dc.subject.other | Microcontroller | en_US |
dc.subject.other | Arduino | en_US |
dc.subject.other | Image processing | en_US |
dc.subject.other | Block processing | en_US |
dc.title | Smart motion detection sensor based on video processing using self-organizing maps | en_US |
dc.type | info:eu-repo/semantics/Article | en_US |
dc.type | article | en_US |
dc.identifier.doi | 10.1016/j.eswa.2016.08.010 | en_US |
dc.identifier.scopus | 2-s2.0-84984831664 | - |
dc.identifier.isi | WOS:000383810800038 | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | #NODATA# | - |
dc.contributor.orcid | 0000-0001-8231-5687 | - |
dc.contributor.orcid | #NODATA# | - |
dc.description.lastpage | 476 | en_US |
dc.relation.volume | 64 | en_US |
dc.investigacion | Ingeniería y Arquitectura | en_US |
dc.type2 | Artículo | en_US |
dc.description.numberofpages | 489 | en_US |
dc.utils.revision | Sí | en_US |
dc.identifier.ulpgc | No | en_US |
dc.contributor.buulpgc | BU-INF | en_US |
dc.description.sjr | 1,433 | |
dc.description.jcr | 3,928 | |
dc.description.sjrq | Q1 | |
dc.description.jcrq | Q1 | |
dc.description.scie | SCIE | |
item.grantfulltext | none | - |
item.fulltext | Sin texto completo | - |
crisitem.author.dept | GIR SIANI: Inteligencia Artificial, Robótica y Oceanografía Computacional | - |
crisitem.author.dept | IU Sistemas Inteligentes y Aplicaciones Numéricas | - |
crisitem.author.orcid | 0000-0002-4397-2905 | - |
crisitem.author.parentorg | IU Sistemas Inteligentes y Aplicaciones Numéricas | - |
crisitem.author.fullName | Ortega Zamorano,Francisco | - |
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