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The ability to form reconstructions beyond line-of-sight view could be transformative in a variety of fields, including search and rescue, autonomous vehicle navigation, and reconnaissance. Most existing active non-line-of-sight (NLOS) imaging methods use data collection steps in which a pulsed laser is directed at several points on a relay surface, one at a time. The prevailing approaches include raster scanning of a rectangular grid on a vertical wall opposite the volume of interest to generate a collection of confocal measurements. These and a recent method that uses a horizontal relay surface are inherently limited by the need for laser scanning. Methods that avoid laser scanning to operate in a snapshot mode are limited to treating the hidden scene of interest as one or two point targets. In this work, based on more complete optical response modeling yet still without multiple illumination positions, we demonstrate accurate reconstructions of foreground objects while also introducing the capability of mapping the stationary scenery behind moving objects. The ability to count, localize, and characterize the sizes of hidden objects, combined with mapping of the stationary hidden scene, could greatly improve indoor situational awareness in a variety of applications.

 

In a built environment, wanting to see without direct line of sight is often due to being outside a doorway. The two vertical edges of the doorway provide occlusions that can be exploited for non-line-of-sight imaging by forming corner cameras. While each corner camera can separately yield a robust 1D reconstruction, joint processing suggests novelties in both forward modeling and inversion. The resulting doorway camera provides accurate and robust 2D reconstructions of the hidden scene. This work provides a novel inversion algorithm to jointly estimate two views of change in the hidden scene, using the temporal difference between photographs acquired on the visible side of the doorway. Successful reconstruction is demonstrated in a variety of real and rendered scenarios, including different hidden scenes and lighting conditions. A Cramer-Rao bound analysis is used to demonstrate the 2D resolving power of the doorway camera over other passive acquisition strategies and to motivate the novel biangular reconstruction grid.