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Authordc.contributor.authorTapia, Juan
Authordc.contributor.authorLópez Droguett, Enrique Andrés
Authordc.contributor.authorValenzuela, Andrés
Authordc.contributor.authorBenalcazar Villavicencio, Daniel Patricio
Authordc.contributor.authorCausa, Leonardo
Authordc.contributor.authorBusch, Christoph
Cita de ítemdc.identifier.citationIEEE Access Volume 9, 2021es_ES
Abstractdc.description.abstractThis paper proposes a new framework to detect, segment, and estimate the localization of the eyes from a periocular Near-Infra-Red iris image under alcohol consumption. This stage will take part in the final solution to measure the fitness for duty. Fitness systems allow us to determine whether a person is physically or psychologically able to perform their tasks. Our segmentation framework is based on an object detector trained from scratch to detect both eyes from a single image. Then, two efficient networks were used for semantic segmentation; a Criss-Cross attention network and DenseNet10, with only 122,514 and 210,732 parameters, respectively. These networks can find the pupil, iris, and sclera. In the end, the binary output eye mask is used for pupil and iris diameter estimation with high precision. Five state-of-the-art algorithms were used for this purpose. A mixed proposal reached the best results. A second contribution is establishing an alcohol behavior curve to detect the alcohol presence utilizing a stream of images captured from an iris instance. Also, a manually labeled database with more than 20k images was created. Our best method obtains a mean Intersection-over-Union of 94.54% with DenseNet10 with only 210,732 parameters and an error of only 1-pixel on average.es_ES
Publisherdc.publisherIEEE-Inst Electrical Electronics Engineerses_ES
Type of licensedc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
Link to Licensedc.rights.uri*
Sourcedc.sourceIEEE Accesses_ES
Keywordsdc.subjectFitness for dutyes_ES
Títulodc.titleSemantic segmentation of periocular near-infra-red eye images under alcohol effectses_ES
Document typedc.typeArtículo de revistaes_ES
dc.description.versiondc.description.versionVersión publicada - versión final del editores_ES
dcterms.accessRightsdcterms.accessRightsAcceso abiertoes_ES
Indexationuchile.indexArtículo de publícación WoSes_ES

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Attribution-NonCommercial-NoDerivs 3.0 United States
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States