Object segmentation by top-down processes

In cluttered scenes, some object boundaries may not be marked by image cues. In such cases, the boundaries must be defined top-down as a result of object recognition. Here we ask if observers can retain the boundaries of several recognized objects in order to segment an unfamiliar object. We generated scenes consisting of neatly stacked objects, and the objects themselves consisted of neatly stacked colored blocks. Because the blocks were stacked the same way within and across objects, there were no visual cues indicating which blocks belonged to which objects. Observers were trained to recognize several objects and we tested whether they could segment a novel object when it was surrounded by these familiar, studied objects. The observer’s task was to count the number of blocks comprising the target object. We found that observers were able to accurately count the target blocks even when the target was surrounded by up to four familiar objects. These results indicate that observers can use the boundaries of recognized objects in order to accurately segment, top-down, a novel object.