Image/source statistics of surfaces in natural scenes

Abstract

Perceiving surfaces in a manner that accords with their physical properties is essential for successful behaviour. Since, however, a given retinal image can have been generated by an infinite variety of natural surfaces with different geometrical and/or physical qualities, the corresponding percepts cannot be determined by the stimulus per se. Rather, resolution of this quandary requires a strategy of vision that incorporates the statistical relationship of the information in retinal images to its sources in representative environments. To examine this probabilistic relationship with respect to the features of object surfaces, we analysed a database of range images in which the distances of all the objects in a series of natural scenes were measured with respect to the image plane by a laser range scanner. By taking any particular scene obtained in this way to be made up of a set of concatenated surface patches, we were able to explore the statistics of scene roughness, size–distance relationships, surface orientation and local curvature, as well as the independent components of natural surfaces. The relevance of these statistics to both perception and the neuronal organization of the underlying visual circuitry is discussed.