To what extent do unique parts influence recognition across changes in viewpoint?

We investigated how varying the number of unique parts within an object influences recognition across changes in viewpoint The stimuli were shaded objects composed of five three-dimensional volumes linked end to end with varying connection angles Of the five volumes, zero, one, three, or five were qualitatively distinct (e g, brick vs cone), the rest being tubes Sequential-matching and naming tasks were used to assess the recognition of these stimuli over rotations in depth Three major results stand out First, regardless of the number of distinct parts, there was increasingly poorer recognition performance with increasing change in viewpoint Second, the impact of viewpoint change for objects with one unique part was less than that for the other objects Third, additional parts beyond a single unique part produced strong viewpoint dependency comparable to that obtained for objects with no distinct parts Thus, visual recognition may be explained by a view-based theory in which viewpoint-specific representations encode both quantitative and qualitative features