Purchase this article with an account.
David Brainard, Ana Radonji; The use of graphics simulations in the study of object color appearance. Journal of Vision 2016;16(12):2. doi: https://doi.org/10.1167/16.12.2.
Download citation file:
© ARVO (1962-2015); The Authors (2016-present)
A central goal in the study of color appearance is to develop and validate models that predict object color appearance from a physical scene description. Ultimately, we seek models that apply for any stimulus, and particularly for stimuli typical of natural viewing. One approach is to study color appearance using real illuminated objects in quasi-natural arrangements. This approach has the advantage that the measurements are likely to capture what happens for natural viewing. It has the disadvantage that it is challenging to manipulate the stimuli parametrically in theoretically interesting ways. At the other extreme, one can choose simplified stimulus sets (e.g., spots of light on uniform backgrounds, or Mondrian configurations). This approach has the advantage that complete characterization of performance within the set may be possible, and one can hope that any principles developed will have general applicability. On the other hand, there is no a priori guarantee that what is learned will indeed be helpful for predicting what happens for real illuminated objects. Here we consider an intermediate choice, the use of physically-accurate graphics simulations. These offer the opportunity for precise stimulus specification and control; particularly interesting is the ability to manipulate explicitly distal (object and illuminant) rather than proximal (image) stimulus properties. They also allow for systematic introduction of complexities typical of natural stimuli, thus making it possible to ask what features of natural viewing affect performance and providing the potential to bridge between the study of simplified stimuli and the study of real illuminated objects.
Meeting abstract presented at VSS 2016
This PDF is available to Subscribers Only