For gesture recognition, it will be possible to determine where your information is complete and where it is not available. All these could be useful for in understanding an active environment. There are scores of papers on recreating three dimensional shape from stereo, shading, motion parallax, sonar arrays, and many other methods. Stereo vision usually suffers from the sparse or unreliable nature of it's evidence. Shape from shading suffers from shadows, multicolored objects, complex lighting conditions, and non-uniform reflectance properties.
Motion parallax has problems in when there is any motion in the scene.
Sonar arrays are not extremely accurate. Because of these limitations, shape recovery has fallen from grace and is thought to be a less important aspect of vision. In the future, I will investigate whether obscurities and one of the afore mentioned methods can produce interesting results. But the thrust of this work is not to recreate an accurate three dimensional model of the environment, but to use the obscurity information to constrain other problems. There has been previous work to derived vacancy spaces, but this primarily used only the information of where an object was to define where things were not.