Emotional content of an image attracts attention more than visually salient features in various signal-to-noise ratio conditions.

Emotional images are processed in a prioritized manner, attracting attention almost immediately. In the present study we used eye tracking to reveal what type of features within neutral, positive, and negative images attract early visual attention: semantics, visual saliency, or their interaction. Semantic regions of interest were selected by observers, while visual saliency was determined using the Graph-Based Visual Saliency model. Images were transformed by adding pink noise in several proportions to be presented in a sequence of increasing and decreasing clarity. Locations of the first two fixations were analyzed. The results showed dominance of semantic features over visual saliency in attracting attention. This dominance was linearly related to the signal-to-noise ratio. Semantic regions were fixated more often in emotional images than in neutral ones, if signal-to-noise ratio was high enough to allow participants to comprehend the gist of a scene. Visual saliency on its own did not attract attention above chance, even in the case of pure noise images. Regions both visually salient and semantically relevant attracted a similar amount of fixation compared to semantic regions alone, or even more in the case of neutral pictures. Results provide evidence for fast and robust detection of semantically relevant features.