Space-based visual attention models and object selection: constraints, problems, and possible solutions.

Abstract

One of the functions of visual attention is the selection of object information. This seems to be in line with an influential group of attentional models that assume that attentional selection is space based. These models assume that the selection of an object in vision is realized by selection of the location of that object. Whether this relatively simple idea of space-based attention and the corresponding, more elaborated space-based models are sufficient to handle selected constraints and problems of object selection is the main issue of this article. The first step toward an answer is to describe the common computational structure of space-based attentional models. Two model classes will be distinguished: capacity-limited models (e.g., Treisman, 1988; LaBerge & Brown, 1989) and models that do not assume a capacity limitation (e.g., Van der Heijden, 1992). Next, three kinds of task and data on object selection are introduced that are especially challenging for space-based models. The first type of data refers to experiments that require selection between overlapping objects. The second type of data concerns the influence of early perceptual grouping--a strong object-defining factor--on late response competition, and the third type consists of a selection task in which a high-level (semantic) attribute defines an object and controls selection. In all three cases, problems of space-based models are analyzed and possible solutions are sketched. Finally, a brief evaluative summary is given.