Early Visual Saliency Based on Isolated Optimal Features.

Under fast viewing conditions, the visual system extracts salient and simplified representations of complex visual scenes. Saccadic eye movements optimize such visual analysis through the dynamic sampling of the most informative and salient regions in the scene. However, a general definition of saliency, as well as its role for natural active vision, is still a matter for discussion. Following the general idea that visual saliency may be based on the amount of local information, a recent constrained maximum-entropy model of early vision, applied to natural images, extracts a set of local optimal information-carriers, as candidate salient features. These features proved to be more informative than others in fast vision, when embedded in simplified sketches of natural images. In the present study, for the first time, these features were presented in isolation, to investigate whether they can be visually more salient than other features, even in the absence of any meaningful global arrangement (contour, line, etc.). In four psychophysics experiments, fast discriminability of a compound of features (target) in comparison with a similar compound of features (distractor) was measured as a function of their number and contrast. Results showed that the saliency predictions from the constrained maximum-entropy model are well verified in the data, even when the features are presented in smaller numbers or at lower contrast. In the eye movements experiment, the target and the distractor compounds were presented in the periphery at different angles. Participants were asked to perform a simple choice-saccade task. Results showed that saccades can select informative features spatially interleaved with features even at the shortest latencies. Saccades' choice accuracy and landing position precision improved with SNR. In conclusion, the features predicted by the reference model, turn out to be more salient than others, despite the lack of any clues coming from a global meaningful structure, suggesting that they get preferential treatment during fast image analysis. Also, peripheral fast visual processing of these informative local features is able to guide gaze orientation. We speculate that active vision is efficiently adapted to maximize information in natural visual scenes.