Really neat! Mirrored objects have been a thorn in computer vision as there have been algorithms that will see the reflected objects as independent objects. Certainly this may help if it is known that a specular object is visible. They do make their job easier however by assuming that the camera and pattern are calibrated. In real life it may be easy to know the camera parameters but the "pattern" may be more difficult especially if all you have is just a single image (of course they make note of this in their conclusion).

I do wonder how far they can take their reconstruction procedure for a generic smooth surface. If the object has a lot of inner-reflections, this will be a lot harder to gain the shape from. For instance, if you have 2 flat mirrors 90 degrees from one another, the extracted shape may end up in the shape of a cross (the relections make it look like you have 4 mirrors instead of two). Anyone have any thoughts as to how they could solve this?