Geisler W S, Chou K L
Center for Vision and Image Sciences, University of Texas, Austin 78712, USA.
Psychol Rev. 1995 Apr;102(2):356-78. doi: 10.1037/0033-295x.102.2.356.
A method for assessing the role of low-level factors in complex tasks is described. The method, which involves comparing simple-discrimination performance and complex-task performance for the same stimuli, was used to assess the role of low-level factors in multiple-fixation visual search. In one experiment, the target and background were composed of line segments that differed in color, orientation, or both; in another, target and background were composed of filtered-noise textures that differed in spatial frequency, orientation, or both. Most of the variance in search time was found to be predictable from the discrimination data, suggesting that low-level factors often play a dominant role in limiting search performance. A signal-detection model is presented that demonstrates how current psychophysical models of visual discrimination might be generalized to obtain a theory that can predict search performance for a wide range of stimulus conditions.
描述了一种评估低层次因素在复杂任务中作用的方法。该方法通过比较相同刺激下的简单辨别性能和复杂任务性能，来评估低层次因素在多次注视视觉搜索中的作用。在一个实验中，目标和背景由颜色、方向或两者都不同的线段组成；在另一个实验中，目标和背景由空间频率、方向或两者都不同的滤波噪声纹理组成。研究发现，搜索时间的大部分方差可从辨别数据中预测出来，这表明低层次因素在限制搜索性能方面往往起主导作用。提出了一个信号检测模型，该模型展示了当前视觉辨别心理物理学模型如何进行推广，以获得一个能够预测广泛刺激条件下搜索性能的理论。
