Recognizing Silhouettes and Shaded Images across Depth Rotation

Abstract

Outline-shape information may be particularly important in the recognition of depth-rotated objects because it provides a coarse shape description which gives first-pass information about the structure of an object. In four experiments, we compared recognition of silhouettes (showing only outline shape) with recognition of fully shaded images of objects, by means of a sequential-matching task. In experiments 1 and 2, the first stimulus was always a shaded image, and the second stimulus was either a shaded image or a silhouette. Recognition costs associated with a change in viewpoint were no greater for silhouettes than they were for shaded images. Experiments 3 and 4 replicated the design of the earlier experiments, but showed a silhouette as the initial stimulus, rather than a shaded image. In these cases, recognition costs associated with a change in viewpoint were greater for silhouettes than for shaded images. Combined, these results indicate that, while visual representations clearly include additional information, outline shape plays an important role in object recognition across depth rotation.

Processing convexity and concavity along a 2-D contour: figure–ground, structural shape, and attention

“…Research has indeed confirmed that this is the case. For instance, object recognition is equivalent for silhouettes and for shaded images (Hayward, 1998;Hayward, Tarr, & Corderoy, 1999;Lloyd-Jones & Luckhurst, 2002). In an extensive study with silhouettes and contours derived from 260 line drawings of everyday objects , a large number remained almost perfectly identifiable (112 stimuli with >90 % correct identification).…”

Outline shape is a mediator of object recognition that is particularly important for living things

“…This similarity in performance on the different stimuli suggests that visual features in the outline shape are important for object recognition. If silhouette recognition were markedly more difficult than recognition of fully shaded images ("shaded objects") in these paradigms, then we would have to conclude that nonsilhouette information, such as surface curvature (including geons) and texture information, is more important for object recognition.In fact, Hayward, Tarr, and Corderoy (1999) have found contributions of both outline contourand non-outlinecontourinformation to objectrecognition across depth rotation.…”

When are viewpoint costs greater for silhouettes than for shaded images?

“…Hayward (1998) used both name priming and sequential matching tasks and found no difference in recognition of rotated objects between shaded image and silhouette depictions. Similarly, in a more systematic study using different object sets and more study-test manipulations, Hayward, Tarr, and Corderoy (1999) found that viewpoint costs (the relative decrement in performance following rotation of an object between study and test) were in general no greater for silhouettes than for shaded images. The implication for theories of object recognition from these results is that perceptual representations of objects might consist primarily, if not exclusively, of components of outline shape.…”

“…For example, Hayward et al (1999) found greater viewpoint costs in a sequential matching task when both images were silhouettes than when either one or both of the stimuli were shaded images. In addition, Lloyd-Jones and Luckhurst (2002) found that although living objects were recognized well using outline information, nonliving things appeared to require internal features.…”