Tuesday, 30.10.2007, 11:30
The image of a curved, specular (mirror-like) surface is a distorted reflection of the environment. Although the recovery of such specular shape from its image appears futile without some knowledge of the environment, the goal of this work is to develop a theoretical and practical framework for solving this shape inference problem when the environment is completely unknown. We show that although this general problem is severely ill-posed, allowing relative object-environment motion induces a dense specular flow in the image plane which can be related to surface shape through a pair of coupled non-linear partial differential equations that are independent on the environment content. We examine the qualitative and geometric properties of these equations and present analytic and numerical methods for recovery of specular shape in several cases.
Joint work with Yair Adato, Ben Gurion University, and Yuriv Vasilyev and Todd Zickler, Harvard University