Cohen Elias H, Singh Manish, Maloney Laurence T
Department of Psychology, Rutgers University, New Brunswick, NJ, USA.
J Vis. 2008 May 23;8(7):6.1-13. doi: 10.1167/8.7.6.
We investigated perceptual segmentation in the context of a perceived-orientation task. Stimuli were dot clusters formed by the union of a large elliptical sub-cluster and a secondary circular sub-cluster. We manipulated the separation between the two sub-clusters, their common dot density, and the size of the secondary sub-cluster. As the separation between sub-clusters increased, the orientation perceived by observers shifted gradually from the global principal axis of the entire cluster to that of the main sub-cluster alone. Thus, with increasing separation, the dots within the secondary sub-cluster were assigned systematically lower weights in the principal-axis computation. In addition, this shift occurred at smaller separations for higher dot densities-consistent with the idea that reliable segmentation is possible with smaller separations when the dot density is high. We propose that the visual system employs a robust statistical estimator in this task and that data points are weighted differentially based on the likelihood that they arose from a separate generative process. However, unlike in standard robust estimation, weights based on residuals are insufficient to characterize human segmentation. Rather, these must be computed based on more comprehensive generative models of dot clusters.
我们在一个感知方向任务的背景下研究了感知分割。刺激物是由一个大的椭圆形子簇和一个次要的圆形子簇合并形成的点簇。我们操纵了两个子簇之间的间距、它们的公共点密度以及次要子簇的大小。随着子簇之间间距的增加，观察者感知到的方向逐渐从整个簇的全局主轴转移到仅主性子簇的主轴。因此，随着间距增加，次要子簇内的点在主轴计算中被系统地赋予较低权重。此外，对于较高的点密度，这种转移在较小的间距时就会发生，这与当点密度高时较小的间距就能实现可靠分割的观点一致。我们提出视觉系统在这项任务中采用了一种稳健的统计估计器，并且数据点根据它们源自单独生成过程的可能性被赋予不同的权重。然而，与标准的稳健估计不同，基于残差的权重不足以描述人类的分割。相反，这些权重必须基于更全面的点簇生成模型来计算。
