Detection of animals in natural images using far peripheral vision

It is generally believed that the acuity of the peripheral visual field is too poor to allow accurate object recognition and, that to be identified, most objects need to be brought into foveal vision by using saccadic eye movements. However, most measures of form vision in the periphery have been done at eccentricities below 10° and have used relatively artificial stimuli such as letters, digits and compound Gabor patterns. Little is known about how such data would apply in the case of more naturalistic stimuli. Here humans were required to categorize briefly flashed (28 ms) unmasked photographs of natural scenes (39° high, and 26° across) on the basis of whether or not they contained an animal. The photographs appeared randomly in nine locations across virtually the entire extent of the horizontal visual field. Accuracy was 93.3% for central vision and decreased almost linearly with increasing eccentricity (89.8% at 13°, 76.1% at 44.5° and 71.2% at 57.5°). Even at the most extreme eccentricity, where the images were centred at 70.5°, subjects scored 60.5% correct. No evidence was found for hemispheric specialization. This level of performance was achieved despite the fact that the position of the image was unpredictable, ruling out the use of precued attention to target locations. The results demonstrate that even high-level visual tasks involving object vision can be performed using the relatively coarse information provided by the peripheral retina.