hide
Free keywords:
-
Abstract:
We previously showed that the human visual system is exquisitely sensitive to local natural image
regularities (Gerhard et al, 2011 Perception 40 ECVP Supplement, 18). However, luminance histogram
features were a very salient cue. Here we focus instead on sensitivity to the local shape regularities in
natural images. Stimuli were textures made of image patches sampled either from natural images or
from a natural image model, where observers had to discriminate the two kinds of textures in a forced
choice task. We used a variety of natural image models that capture varying degrees of higher-order
correlations. We removed salient luminance cues from the textures and measured discriminability of the
models from natural images when shape was the only cue. Above chance performance with patches
4x4 pixels in size and larger indicated sensitivity to higher-order natural image correlations associated
with shape. A surprising pattern of discriminability also emerged which indicated an advantage of the
independent components analysis model in capturing salient shape content, even though it captures less
of the overall higher-order correlations than other models tested. We also analyzed the contribution
of different principle components to discrimination performance in order to develop a preliminary
mechanistic explanation using responses of spatial frequency filter banks.
