Eight-Channel Multispectral Image Database for Saliency Prediction Martínez Domingo, Miguel Ángel Nieves Gómez, Juan Luis Valero Benito, Eva María Attention Multispectral database Saliency Eye-tracking Computer vision Spectral imaging Color imaging Saliency 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. 2021-03-05T13:08:55Z 2021-03-05T13:08:55Z 2021 info:eu-repo/semantics/article Martínez-Domingo, M.Á.; Nieves, J.L.; Valero, E.M. Eight-Channel Multispectral Image Database for Saliency Prediction. Sensors 2021, 21, 970. https:// doi.org/10.3390/s21030970 http://hdl.handle.net/10481/66937 10.3390/s21030970 eng http://creativecommons.org/licenses/by/3.0/es/ info:eu-repo/semantics/openAccess Atribución 3.0 España MDPI