Automatic analysis of ocular focus detection based on visual features

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dc.contributor.authorNASCIMENTO, D. O.
dc.contributor.authorOLIVEIRA, G. A.
dc.contributor.authorLOPES, Guilherme
dc.contributor.authorRODRIGUES, Paulo
dc.date.accessioned2019-08-17T20:00:30Z
dc.date.available2019-08-17T20:00:30Z
dc.date.issued2019
dc.description.abstractalternativeThe human eye focusing is one of the most important tasks in the cognitive process of scene interpretation. The ability to estimate the focusing regions may vary according to the used algorithm and the image being analyzed, bringing a satisfactory efficiency in a specific set of images. This paper studies 9 methods proposed in the last decade, using 21 different features, discovering relations between the information within the images and the efficiency of the prediction. Using a supervised database, this paper shows that dispersion features for intensity data and color are more significant for the method efficiency than those based only on the average of the data. Besides, this paper proposes and analyses the capacity of Machine Learning techniques in identifying patterns inside the original images and selecting the most appropriate method to estimate focusing pointsen
dc.description.abstractalternativeThe human eye focusing is one of the most important tasks in the cognitive process of scene interpretation. The ability to estimate the focusing regions may vary according to the used algorithm and the image being analyzed, bringing a satisfactory efficiency in a specific set of images. This paper studies 9 methods proposed in the last decade, using 21 different features, discovering relations between the information within the images and the efficiency of the prediction. Using a supervised database, this paper shows that dispersion features for intensity data and color are more significant for the method efficiency than those based only on the verage of the data. Besides, this paper proposes and analyses the capacity of Machine Learning techniques in identifying patterns inside the original images and selecting the most appropriate method to estimate focusing points.en
dc.description.firstpage9396
dc.description.lastpage9410
dc.description.volume6
dc.identifier.citationNASCIMENTO, D. O.; OLIVEIRA, G. A.; LOPES, Guilherme.; RODRIGUES, Paulo. Automatic analysis of ocular focus detection based on visual features. Journal of Multidisciplinary Engineering Science and Technology (JMEST), v. 6, p. 9396, 2019.
dc.identifier.issn2458-9403
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/1011
dc.identifier.urlhttp://www.jmest.org/wp-content/uploads/JMESTN42352809.pdf
dc.relation.ispartofJournal of Multidisciplinary Engineering Science and Technology (JMEST)
dc.rightsAcesso Aberto
dc.subject.otherlanguageAutomatic focus detectionen
dc.subject.otherlanguageComputational visionen
dc.subject.otherlanguageAutomatic focus detectionen
dc.subject.otherlanguageFocus analysisen
dc.subject.otherlanguageComputational visionen
dc.titleAutomatic analysis of ocular focus detection based on visual featurespt_BR
dc.typeArtigopt_BR
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