Semizer Yelda, Michel Melchi M
Department of Psychology, Rutgers University, New Brunswick, NJ, USA.
J Vis. 2019 Apr 1;19(4):1. doi: 10.1167/19.4.1.
Although studies of visual search have repeatedly demonstrated that visual clutter impairs search performance in natural scenes, these studies have not attempted to disentangle the effects of search set size from those of clutter per se. Here, we investigate the effect of natural image clutter on performance in an overt search for categorical targets when the search set size is controlled. Observers completed a search task that required detecting and localizing common objects in a set of natural images. The images were sorted into high- and low-clutter conditions based on the clutter metric by Bravo and Farid (2008). The search set size was varied independently by fixing the number and positions of potential targets across set size conditions within a block of trials. Within each fixed set size condition, search times increased as a function of increasing clutter, suggesting that clutter degrades overt search performance independently of set size.
尽管视觉搜索研究反复表明,视觉杂波会损害自然场景中的搜索性能,但这些研究并未尝试将搜索集大小的影响与杂波本身的影响区分开来。在这里,我们研究了在控制搜索集大小的情况下,自然图像杂波对公开搜索类别目标时的性能的影响。观察者完成了一项搜索任务,该任务需要在一组自然图像中检测并定位常见物体。根据Bravo和Farid(2008年)的杂波度量标准,将图像分为高杂波和低杂波条件。通过在一组试验中固定潜在目标的数量和位置,在不同的集大小条件下独立改变搜索集大小。在每个固定的集大小条件下,搜索时间随着杂波的增加而增加,这表明杂波会独立于集大小而降低公开搜索性能。