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dc.contributor.authorMartínez Domingo, Miguel Ángel 
dc.contributor.authorNieves Gómez, Juan Luis 
dc.contributor.authorValero Benito, Eva María
dc.identifier.citationMartínez-Domingo, M.Á.; Nieves, J.L.; Valero, E.M. Eight-Channel Multispectral Image Database for Saliency Prediction. Sensors 2021, 21, 970. https://
dc.description.abstractSaliency prediction is a very important and challenging task within the computer vision community. Many models exist that try to predict the salient regions on a scene from its RGB image values. Several new models are developed, and spectral imaging techniques may potentially overcome the limitations found when using RGB images. However, the experimental study of such models based on spectral images is difficult because of the lack of available data to work with. This article presents the first eight-channel multispectral image database of outdoor urban scenes together with their gaze data recorded using an eyetracker over several observers performing different visualization tasks. Besides, the information from this database is used to study whether the complexity of the images has an impact on the saliency maps retrieved from the observers. Results show that more complex images do not correlate with higher differences in the saliency maps obtained.es_ES
dc.description.sponsorshipSpanish Ministry of Science, Innovation, and Universities (MICINN) RTI2018-094738-B-I00es_ES
dc.description.sponsorshipEuropean Commissiones_ES
dc.rightsAtribución 3.0 España*
dc.subjectAttention es_ES
dc.subjectMultispectral databasees_ES
dc.subjectComputer visiones_ES
dc.subjectSpectral imaginges_ES
dc.subjectColor imaginges_ES
dc.titleEight-Channel Multispectral Image Database for Saliency Predictiones_ES

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Atribución 3.0 España
Except where otherwise noted, this item's license is described as Atribución 3.0 España