Neri Peter, Heeger David J
Department of Psychology, Serra Mall 450, Stanford University, Stanford California 94305, USA.
Nat Neurosci. 2002 Aug;5(8):812-6. doi: 10.1038/nn886.
Our visual system constantly selects salient features in the environment, so that only those features are attended and targeted by further processing efforts to identify them. Models of feature detection hypothesize that salient features are localized based on contrast energy (local variance in intensity) in the visual stimulus. This hypothesis, however, has not been tested directly. We used psychophysical reverse correlation to study how humans detect and identify basic image features (bars and short line segments). Subjects detected a briefly flashed 'target bar' that was embedded in 'noise bars' that randomly changed in intensity over space and time. By studying how the intensity of the noise bars affected performance, we were able to dissociate two processing stages: an early 'detection' stage, whereby only locations of high-contrast energy in the image are selected, followed (after approximately 100 ms) by an 'identification' stage, whereby image intensity at selected locations is used to determine the identity (whether bright or dark) of the target.
我们的视觉系统不断地在环境中选择显著特征，以便只有那些特征会被关注，并通过进一步的处理努力来识别它们。特征检测模型假设，显著特征是基于视觉刺激中的对比度能量（强度的局部方差）进行定位的。然而，这一假设尚未得到直接验证。我们使用心理物理学反向关联法来研究人类如何检测和识别基本图像特征（线条和短线段）。受试者检测出一个短暂闪现的“目标线条”，它被嵌入在“噪声线条”中，这些“噪声线条”在空间和时间上的强度随机变化。通过研究噪声线条的强度如何影响表现，我们能够区分两个处理阶段：一个早期的“检测”阶段，在此阶段仅选择图像中高对比度能量的位置，随后（大约100毫秒后）是一个“识别”阶段，在此阶段，所选位置的图像强度用于确定目标的身份（亮或暗）。
