Distance v.s. Resolution: Neuromapping of Effective Resolution onto Physical Distance

The main focus of this work is on determining the effective resolution of a face image on the retina when the face is at a particular distance from the eye. Despite its straightforward articulation, arriving at a satisfactory solution might be unexpectedly challenging. The relationship between viewing distance and effective resolution cannot be easily obtained through Snellen acuity, contrast sensitivity, photoreceptor packing density or ganglion cell convergence rate in the retina. We used theoretical modelling to establish preliminary guidelines and then tested them empirically. We showed participants a 2 x 2 array of images in different resolutions at various viewing distances. At each distance, participants were expected to perform an "odd one out" task, identifying the image that was blurrier than the other three. As the study progressed, viewing distance was gradually reduced. The data collected enabled us to determine the upper and lower limits of the available effective resolution for human vision under normal conditions, as a function of viewing distance. Notably, human performance in blur detection is superior to what a theoretical model based on projected image size, cone density, and foveal extent predicts, especially at close ranges. Therefore, we propose that future theoretical models must account for non-uniform in-fovea density and the less pronounced decline in acuity outside the fovea to establish a reliable relationship between viewing distance and perceived image characteristics. The mapping allows for a direct comparison of human face recognition performance across different levels of blur and viewing distance. It also enables us to systematically compare human performance to that of machine vision systems using resolution as a common factor.