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BEING A SOUTHPAW MAKES FINDING A DECENT BASS A challenge. When I started playing the bass in the summer of 1990, I first did the Hendrix thing by flipping the [...]

Symmetry is usually easier to detect within a single object than in two objects (one-object advantage), while the reverse is true for repetition (two-objects advantage). This interaction between regularity and number of objects could reflect an intrinsic property of encoding spatial relations within and across objects or it could reflect a matching strategy. To test this, regularities between two contours (belonging to a single object or two objects) had to be detected in two experiments. Projected three-dimensional (3-D) objects rotated in depth were used to disambiguate figure-ground segmentation and to make matching based on simple translations of the two-dimensional (2-D) contours unlikely. Experiment 1 showed the expected interaction between regularity and number of objects. Experiment 2 used two-objects displays only and prevented a matching strategy by also switching the positions of the two objects. Nevertheless, symmetry was never detected more easily than repetition in these two-objects displays. We conclude that structural coding, not matching strategies, underlies the one-object advantage for symmetry and the two-objects advantage for repetition.

Abstract: In visual perception, part segmentation of an object is considered to be guided by image-based properties, such as occurrences of deep concavities in the outer contour. However, object-based properties can also provide information regarding segmentation. In this study, outer contours and interpretations of object configurations were manipulated to examine differences between image-based and object-based segmentation in a visual search task. We found that locating a two-dimensional object configuration with deep concavities in the outer contour depends on the type of outer contour of the surrounding distractors. In addition, locating a three-dimensional object configuration was harder when it was surrounded by object-based-disconnected distractors, as compared with object-based-connected distractors, regardless of image-based connections in these distractors. We conclude that segmentation based on the outer contours of a target facilitates its localization. However, when three-dimensional information is available, segmentation strongly depends on object-based properties, rather than on image-based properties.

Abstract: In two matching tasks, participants had to match two images of object pairs. Image-based (IB) connectedness refers to connectedness between the objects in an image. Object-based (OB) connectedness refers to connectedness between the interpreted objects. In Experiment 1, a monocular depth cue (shadow) was used to distinguish different relation types between object pairs. Three relation types were created: IB/OB-connected objects, IB/OB-disconnected objects, and IB-connected/OB-disconnected objects. It was found that IB/OB-connected objects were matched faster than IB/OB-disconnected objects. Objects that were IB-connected/OB-disconnected were matched equally to IB/OB-disconnected objects. In Experiment 2, stereoscopic presentation was used. With relation types comparable to those in Experiment 1, it was again found that OB connectedness determined speed of matching, rather than IB connectedness. We conclude that matching of projections of three-dimensional objects depends more on OB connectedness than on IB connectedness.