García Díaz, AntónFernández Vidal, Xosé RamónPardo López, Xosé ManuelDosil Lago, Raquel2024-02-122024-02-122009Garcia-Diaz, A., Fdez-Vidal, X.R., Pardo, X.M., Dosil, R. (2009). Decorrelation and Distinctiveness Provide with Human-Like Saliency. In: Blanc-Talon, J., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2009. Lecture Notes in Computer Science, vol 5807. Springer, Berlin, Heidelberghttp://hdl.handle.net/10347/32755This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-642-04697-1_32In this work, we show the capability of a new model of saliency, of reproducing remarkable psychophysical results. The model presents low computational complexity compared to other models of the state of the art. It is based in biologically plausible mechanisms: the decorrelation and the distinctiveness of local responses. Decorrelation of scales is obtained from principal component analysis of multiscale low level features. Distinctiveness is measured through the Hotelling’s T2 statistic. The model is conceived to be used in a machine vision system, in which attention would contribute to enhance performance together with other visual functions. Experiments demonstrate the consistency with a wide variety of psychophysical phenomena, that are referenced in the visual attention modeling literature, with results that outperform other state of the art models.engCC BY-NC-ND 4.0http://creativecommons.org/licenses/by-nc-nd/4.0/DecorrelationDistinctivenessconference output10.1007/978-3-642-04697-1_32open access