SPATIAL-FREQUENCY ANALYSIS IN THE PERCEPTION OF PERSPECTIVE DEPTH

We investigate the psychophysical and computational processes underlyi ng the perception of depth from texture cues in perspective projection s. In particular, we analyse the similarities between the processes as sociated with perspective and orthographic projections. Based on a ser ies of psychophysical experiments using white noise stimuli presented in perspective projection, we suggest that the visual system may chara cterize the spatial-frequency spectrum by the average peak frequency ( APF), which is the same characteristic as that used in orthographic pr ojections. We demonstrate that normalization of the APF yields an esti mate of depth in perspective projection. Our previous studies suggest that the APF is used in orthographic projections, where the output of the normalization process represents a linear approximation of surface slant. Based on these results, together with previous psychophysical evidence, we propose a neural network model of shape-from-texture for the perspective view. Simulations of the model show qualitative agreem ent with human perception over a range of real and artificial stimuli.