Non-line-of-sight, or NLOS imaging, is a technique that allows a device (such as a camera) to see objects that are not visible to its line of sight. This is made possible through the use of light pulses, which will bounce off from surfaces, and then go back to the camera’s sources. Algorithms will then analyze the length of time it took these reflections to go back to the camera, and then proceed to create an image based on the information.
Scientists have been refining this technique over the years, but it had one weakness: it needed large reflective surfaces. However, researchers at the Stanford Computational Imaging Lab, may have overcome this weakness with their keyhole imaging technique. The results are worse than previous NLOS techniques, though, but the images generated are still enough in order for a person to make an educated guess on what the object is.
The research could one day provide a way for police or the military to assess the risks of entering a room before actually breaking down the door and storming their way inside, using nothing but a small crack in the wall or a gap around a window or doorway. The new technique could also provide new techniques for autonomous navigation systems to spot hidden hazards long before they become a threat in situations where the previous NLOS techniques weren’t practical given the environment.
(Image Credit: Stanford Computational Engineering Lab)