Sometimes the thing that we want to see is hidden behind something else. A neighboring vehicle on the road might block a motorist's view of a pedestrian that's about to cross the street. Trees might severely hamper a drone's ability to navigate through a forest by occluding the drone's field-of-view in almost every direction. Even the front-facing surface of any opaque object will block our view of the object's back-facing surface.
While we can't view hidden objects directly, sometimes we can learn about them from more indirect cues. In this paper we exploit the fact that hidden objects can still cast shadows onto surfaces that we can see. Shadows are very informative about object shape, particularly if the position of the light source is also known.
We use a laser pointer to project laser spots onto visible surfaces lying to one side of the hidden space. These laser spots act as scannable, "virtual" point sources of light. We use an RGB or RBG-D camera to observe the resulting shadows that hidden objects cast onto surfaces that lie on the opposite side of the hidden space. After illuminating multiple laser spots and subsequently observing multiple sets of shadows, we use a space-carving algorithm to extract the detailed, 3D shapes of objects lying within the hidden space.