Rothkegel et al. 10 to be repeated in 44% of all trials. All analyses were conducted separately for the trials with and without a repetition of the second fixation check and there were no systematic differences. Thus for the analyses in this article we used fixations from all trials. Data preprocessing and saccade detection . For saccade detection we applied a velocity- based algorithm (Engbert & Kliegl, 2003; Engbert & Mergenthaler, 2006). Saccades had a minimum amplitude of 0 . 58 ◦ and exceeded the average velocity during a trial by 6 standard (median-based) deviations for at least 6 data samples (6 ms). The epoch between two subsequent saccades was defined as a fixation. The number of fixations for further analyses was 47 330. Data Analysis Figure 2 . Objective categorizing of images. (a) Example of an image with right focus. (b) Experimental density map of fixations, estimated using a Gaussian kernel with bandwith σ = 2 . 56 ◦ according to Scott’s rule. (c) Output from the Judd saliency model, without distance- to-center analysis and face/object detection. (d) Output from the graph based visual saliency (GBVS) model. (a) (b) (c) (d)