Viewpoint dependence and scene context effects generalize to depth rotated three-dimensional objects.

Viewpoint effects on object recognition interact with object-scene consistency effects. While recognition of objects seen from "noncanonical" viewpoints (e.g., a cup from below) is typically impeded compared to processing of objects seen from canonical viewpoints (e.g., the string-side of a guitar), this effect is reduced by meaningful scene context information. In the present study we investigated if these findings established by using photographic images, generalize to strongly noncanonical orientations of three-dimensional (3D) models of objects. Using 3D models allowed us to probe a broad range of viewpoints and empirically establish viewpoints with very strong noncanonical and canonical orientations. In Experiment 1, we presented 3D models of objects from six different viewpoints (0°, 60°, 120°, 180° 240°, 300°) in color (1a) and grayscaled (1b) in a sequential matching task. Viewpoint had a significant effect on accuracy and response times. Based on the viewpoint effect in Experiments 1a and 1b, we could empirically determine the most canonical and noncanonical viewpoints from our set of viewpoints to use in Experiment 2. In Experiment 2, participants again performed a sequential matching task, however now the objects were paired with scene backgrounds which could be either consistent (e.g., a cup in the kitchen) or inconsistent (e.g., a guitar in the bathroom) to the object. Viewpoint interacted significantly with scene consistency in that object recognition was less affected by viewpoint when consistent scene information was provided, compared to inconsistent information. Our results show that scene context supports object recognition even when using extremely noncanonical orientations of depth rotated 3D objects. This supports the important role object-scene processing plays for object constancy especially under conditions of high uncertainty.