Zaidi Qasim, Bostic Marques
State University of New York, College of Optometry, Department of Vision Sciences, 33 West 42nd Street, New York, NY 10036-8003, USA.
Vision Res. 2008 Nov;48(26):2673-81. doi: 10.1016/j.visres.2008.06.026. Epub 2008 Aug 9.
We measured accuracy of object identification across illuminations on the basis of color cues. Four similarly shaped real objects, three of the same reflectance, were separated into pairs under distinct colored real lights. Observers were asked to pick the odd object. Correct and incorrect identifications formed systematic patterns that could not be explained by color-constancy, contrast-constancy, inverse-optics or neural-signal matching algorithms. The pattern of results were simulated by an algorithm that purposely made the incorrect assumption that color constancy holds, and used similarity between perceived object colors, along the difference vector between illuminant colors, to identify objects of the same reflectance across illuminants. The visual system may use this suboptimal strategy because the computational costs of an optimal strategy outweigh the benefits of more accurate performance.
我们基于颜色线索测量了不同光照条件下物体识别的准确性。四个形状相似的真实物体，其中三个具有相同的反射率，在不同颜色的真实灯光下被分成两两一组。要求观察者挑选出不同的物体。正确和错误识别形成了系统的模式，这些模式无法用颜色恒常性、对比度恒常性、逆光学或神经信号匹配算法来解释。结果模式由一种算法模拟，该算法故意做出颜色恒常性成立的错误假设，并利用感知物体颜色之间的相似性，沿着光源颜色之间的差异向量，来识别不同光照条件下具有相同反射率的物体。视觉系统可能会采用这种次优策略，因为最优策略的计算成本超过了更准确表现所带来的好处。
