Stuart G W, Bossomaier T R, Johnson S
Centre for Visual Science, Australian National University, Canberra.
Perception. 1993;22(10):1175-93. doi: 10.1068/p221175.
Information about the visual angle size of objects is important for maintaining object constancy with variations in viewing distance. Although human observers are quite accurate at judging spatial separations (or cross-sectional size), they are prone to error when there are other spans nearby, as in classical illusions such as the Müller-Lyer illusion. It is possible to reconcile these aspects of size perception by assuming that the size domain is sampled sparsely. It was shown by means of a visual search procedure that the size of objects is processed preattentively and in parallel across the visual field. It was demonstrated that an object's size, rather than its boundary curvature or spatial-frequency content, provides the basis for parallel visual search. It was also shown that texture borders could be substituted for luminance borders, indicating that object boundaries at the relevant spatial scale provide the input to size perception. Parallel processing imposes a severe computational constraint which provides support for the assumption of sparse sampling. An economical model based on several broadly tuned layers of size detectors is proposed to account for the parallel extraction of size, the Weberian behaviour of size discrimination, and the occurrence of strong interference effects in the size domain.
关于物体视角大小的信息对于在观察距离变化时保持物体恒常性很重要。尽管人类观察者在判断空间间隔(或横截面大小)方面相当准确,但当附近存在其他跨度时,他们容易出错,就像在诸如缪勒 - 莱尔错觉等经典错觉中那样。通过假设大小域被稀疏采样,可以协调大小感知的这些方面。通过视觉搜索程序表明,物体的大小在整个视野中是在注意前并行处理的。结果表明,物体的大小而非其边界曲率或空间频率内容为并行视觉搜索提供了基础。还表明纹理边界可以替代亮度边界,这表明在相关空间尺度上的物体边界为大小感知提供了输入。并行处理施加了严格的计算约束,这为稀疏采样的假设提供了支持。提出了一个基于几个广泛调谐的大小探测器层的经济模型,以解释大小的并行提取、大小辨别中的韦伯行为以及大小域中强烈干扰效应的出现。