Object recognition in dense clutter.

Abstract

Observers in recognition experiments invariably view objects against a blank background, whereas observers of real scenes sometimes view objects against dense clutter. In this study, we examined whether an object's background affects the information used for recognition. Our stimuli consisted of color photographs of everyday objects. The photographs were organized either as a sparse array, as is typical of a visual search experiment, or as high density clutter, such as might be found in a toy chest, a handbag, or a kitchen drawer. The observer's task was to locate an animal, vehicle, or food target in the stimulus. We varied the information in the stimuli by convolving them with a low-pass filter (blur) or a high-pass filter (edge) or converting them to grayscale. In two experiments, we found that the blur and edge manipulations produced a modest decrement in performance with the sparse arrangement but a severe decrement in performance with the clutter arrangement. These results indicate that the information used for recognition depends on the object's background. Thus, models of recognition that have been developed for isolated objects may not generalize to objects in dense clutter.