Scene perception: Detecting and judging objects undergoing relational violations
- 1 April 1982
- journal article
- Published by Elsevier BV in Cognitive Psychology
- Vol. 14 (2), 143-177
- https://doi.org/10.1016/0010-0285(82)90007-x
Abstract
Five classes of relations between an object and its setting can characterize the organization of objects into real-world scenes. The relations are (1) Interposition (objects interrupt their background), (2) Support (objects tend to rest on surfaces), (3) Probability (objects tend to be found in some scenes but not others), (4) Position (given an object is probable in a scene, it often is found in some positions and not others), and (5) familiar Size (objects have a limited set of size relations with other objects). In two experiments subjects viewed brief (150 msec) presentations of slides of scenes in which an object in a cued location in the scene was either in a normal relation to its background or violated from one to three of the relations. Such objects appear to (1) have the background pass through them, (2) float in air, (3) be unlikely in that particular scene, (4) be in an inappropriate position, and (5) be too large or too small relative to the other objects in the scene. In Experiment I, subjects attempted to determine whether the cued object corresponded to a target object which had been specified in advance by name. With the exception of the Interposition violation, violation costs were incurred in that the detection of objects undergoing violations was less accurate and slower than when those same objects were in normal relations to their setting. However, the detection of objects in normal relations to their setting (innocent bystanders) was unaffected by the presence of another object undergoing a violation in that same setting. This indicates that the violation costs were incurred not because of an unsuccessful elicitation of a frame or schema for the scene but because properly formed frames interfered with (or did not facilitate) the perceptibility of objects undergoing violations. As the number of violations increased, target detectability generally decreased. Thus, the relations were accessed from the results of a single fixation and were available sufficiently early during the time course of scene perception to affect the perception of the objects in the scene. Contrary to expectations from a bottom-up account of scene perception, violations of the pervasive physical relations of Support and Interposition were not more disruptive on object detection than the semantic violations of Probability, Position and Size. These are termed semantic because they require access to the referential meaning of the object. In Experiment II, subjects attempted to detect the presence of the violations themselves. Violations of the semantic relations were detected more accurately than violations of Interposition and at least as accurately as violations of Support. As the number of violations increased, the detectability of the incongruities between an object and its setting increased. These results provide converging evidence that semantic relations can be accessed from the results of a single fixation. In both experiments information about Position was accessed at least as quickly as information on Probability. Thus in Experiment I, the interference that resulted from placing a fire hydrant in a kitchen was not greater than the interference from placing it on top of a mail ☐ in a street scene. Similarly, violations of Probability in Experiment II were not more detectable than violations of Position. Thus, the semantic relations which were accessed included information about the detailed interactions among the objects—information which is more specific than what can be inferred from the general setting. Access to the semantic relations among the entities in a scene is not deferred until the completion of spatial and depth processing and object identification. Instead, an object's semantic relations are accessed simultaneously with its physical relations as well as with its own identification.Keywords
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