Brainard David H, Cottaris Nicolas P, Radonjić Ana
Department of Psychology, University of Pennsylvania, Philadelphia, PA 19104, USA.
Interface Focus. 2018 Aug 6;8(4):20180012. doi: 10.1098/rsfs.2018.0012. Epub 2018 Jun 15.
Perceived object colour and material help us to select and interact with objects. Because there is no simple mapping between the pattern of an object's image on the retina and its physical reflectance, our perceptions of colour and material are the result of sophisticated visual computations. A long-standing goal in vision science is to describe how these computations work, particularly as they act to stabilize perceived colour and material against variation in scene factors extrinsic to object surface properties, such as the illumination. If we take seriously the notion that perceived colour and material are useful because they help guide behaviour in natural tasks, then we need experiments that measure and models that describe how they are used in such tasks. To this end, we have developed selection-based methods and accompanying perceptual models for studying perceived object colour and material. This focused review highlights key aspects of our work. It includes a discussion of future directions and challenges, as well as an outline of a computational observer model that incorporates early, known, stages of visual processing and that clarifies how early vision shapes selection performance.
感知到的物体颜色和材质有助于我们选择物体并与之互动。由于物体在视网膜上的图像模式与其物理反射率之间不存在简单的映射关系,我们对颜色和材质的感知是复杂视觉计算的结果。视觉科学中长期以来的一个目标是描述这些计算是如何工作的,特别是当它们用于稳定感知到的颜色和材质,以抵御物体表面属性之外的场景因素(如光照)的变化时。如果我们认真对待这样一种观点,即感知到的颜色和材质是有用的,因为它们有助于指导自然任务中的行为,那么我们就需要进行测量的实验和描述它们在这些任务中如何被使用的模型。为此,我们开发了基于选择的方法以及用于研究感知到的物体颜色和材质的相关感知模型。这篇重点综述突出了我们工作的关键方面。它包括对未来方向和挑战的讨论,以及一个计算观察者模型的概述,该模型纳入了视觉处理的早期已知阶段,并阐明了早期视觉如何塑造选择性能。