Purchase this article with an account.
Roland W. Fleming, Antonio Torralba, Edward H. Adelson; Specular reflections and the perception of shape. Journal of Vision 2004;4(9):10. doi: 10.1167/4.9.10.
Download citation file:
© 2017 Association for Research in Vision and Ophthalmology.
Many materials, including leaves, water, plastic, and chrome exhibit specular reflections. It seems reasonable that the visual system can somehow exploit specular reflections to recover three-dimensional (3D) shape. Previous studies (e.g., J. T. Todd & E. Mingolla, 1983; J. F. Norman, J. T. Todd, & G. A. Orban, 2004) have shown that specular reflections aid shape estimation, but the relevant image information has not yet been isolated. Here we explain how specular reflections can provide reliable and accurate constraints on 3D shape. We argue that the visual system can treat specularities somewhat like textures, by using the systematic patterns of distortion across the image of a specular surface to recover 3D shape. However, there is a crucial difference between textures and specularities: In the case of textures, the image compressions depend on the first derivative of the surface depth (i.e., surface orientation), whereas in the case of specularities, the image compressions depend on the second derivative (i.e., surfaces curvatures). We suggest that this difference provides a cue that can help the visual system distinguish between textures and specularities, even when present simultaneously. More importantly, we show that the dependency of specular distortions on the second derivative of the surface leads to distinctive fields of image orientation as the reflected world is warped across the surface. We find that these “orientation fields” are (i) diagnostic of 3D shape, (ii) remain surprisingly stable when the world reflected in the surface is changed, and (iii) can be extracted from the image by populations of simple oriented filters. Thus the use of specular reflections for 3D shape perception is both easier and more reliable than previous computational work would suggest.
This PDF is available to Subscribers Only