Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/46497
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dc.contributor.authorQuesada-Arencibia, Alexisen_US
dc.contributor.authorMoreno-Díaz, Robertoen_US
dc.contributor.authorAleman-Flores, Miguelen_US
dc.date.accessioned2018-11-23T05:12:06Z-
dc.date.available2018-11-23T05:12:06Z-
dc.date.issued2003en_US
dc.identifier.issn0232-9298en_US
dc.identifier.urihttp://hdl.handle.net/10553/46497-
dc.description.abstractIn this paper we present a working vision system for estimating size, location and motion of an object by using a set of randomly distributed receptive fields on a retina. The approach used here differs from more conventional ones in which the receptive fields are arranged in a geometric pattern. From the input level, computations are performed in parallel in two different channels: one for purely spatial properties, the other for time-space analysis, and are then used at a subsequent level to yield estimates of the size and centre of gravity of an object and the speed and direction of motion. Movement analysis refining is implemented by a lateral interaction (spatial) and memory (temporal) schemes in which direction and speed are used to build a trajectory. The different parameters involved (receptive field size, memory weighting function, number of cells) are tested for different speeds and the results compared, yielding new insights on the functioning of the living retina and suggesting ideas for improving the artificial system.en_US
dc.languageengen_US
dc.relation.ispartofSystems Analysis Modelling Simulationen_US
dc.sourceSystems Analysis Modelling Simulation [ISSN 0232-9298], v. 43 (9), p. 1271-1279en_US
dc.subject120304 Inteligencia artificialen_US
dc.subject.otherLateral inhibitionen_US
dc.subject.otherMotion analysisen_US
dc.subject.otherReceptive fielden_US
dc.subject.otherTime integrationen_US
dc.titleA two-channel artificial vision system for motion analysisen_US
dc.typeinfo:eu-repo/semantics/Articlees
dc.typeArticlees
dc.identifier.doi10.1080/02329290310001600327
dc.identifier.scopus33746371661-
dc.contributor.authorscopusid13006053800-
dc.contributor.authorscopusid24543463600-
dc.contributor.authorscopusid55892084700-
dc.description.lastpage1279-
dc.identifier.issue9-
dc.description.firstpage1271-
dc.relation.volume43-
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.date.coverdateSeptiembre 2003
dc.identifier.ulpgces
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.author.deptGIR IUCES: Computación inteligente, percepción y big data-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.deptGIR IUCES: Computación inteligente, percepción y big data-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptGIR IUCES: Centro de Tecnologías de la Imagen-
crisitem.author.deptIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.deptDepartamento de Informática y Sistemas-
crisitem.author.orcid0000-0002-8313-5124-
crisitem.author.orcid0000-0002-5314-6033-
crisitem.author.orcid0000-0002-9258-0086-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.parentorgIU de Cibernética, Empresa y Sociedad (IUCES)-
crisitem.author.fullNameQuesada Arencibia, Francisco Alexis-
crisitem.author.fullNameMoreno Díaz, Roberto-
crisitem.author.fullNameAlemán Flores, Miguel-
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