Parallel visual coding in three dimensions.

Evidence from visual-search experiments is discussed that indicates that there is spatially parallel encoding based on three-dimensional (3-D) spatial relations between complex image features. In one paradigm, subjects had to detect an odd part of cube-like figures, formed by grouping of corner junctions. Performance with cube-like figures was unaffected by the number of corner junctions present, though performance was affected when the corners did not configure into a cube. It is suggested from the data that junctions can be grouped to form 3-D shapes in a spatially parallel manner. Further, performance with cube-like figures was more robust to noncollinearity between junctions than was performance when junctions grouped to form two-dimensional planes. In the second paradigm, subjects searched for targets defined by their size. Performance was affected by a size illusion, induced by linear-perspective cues from local background neighbourhoods. Search was made more efficient when the size illusion was consistent with the real size difference between targets and nontargets, and it was made less efficient when the size illusion was inconsistent with the real size difference. This last result occurred even though search was little affected by the display size in a control condition. We suggest that early, parallel visual processes are influenced by 3-D spatial relations between visual elements, that grouping based on 3-D spatial relations is relatively robust to noncollinearity between junctions, and that, at least in some circumstances, 3-D relations dominate those coded in two-dimensions.