The researchers are focused on autonomous vehicle applications, with the goal of using extremely sensitive lasers that can reflect off nearby objects to see around corners and produce images of objects hidden from view. While some autonomous vehicles are already equipped with lasers for detecting objects around the car, the researchers see other opportunities such as being able to see through foliage from aerial vehicles or giving rescue teams the ability to find people blocked from view by walls and rubble.
"It sounds like magic," says Gordon Wetzstein, assistant professor of electrical engineering and senior author of a paper describing the work, "but the idea of non-line-of-sight imaging is actually feasible."
The researchers are not the first to develop a method for bouncing lasers around corners to capture images of objects. However, they say, their research advances previous efforts by using an extremely efficient and effective algorithm they developed for processing the final image.
"A substantial challenge in non-line-of-sight imaging is figuring out an efficient way to recover the 3-D structure of the hidden object from the noisy measurements," says David Lindell, graduate student in the Stanford Computational Imaging Lab and co-author of the paper. "I think the big impact of this method is how computationally efficient it is."
To create their system, the researchers used a laser set next to a highly sensitive photon detector, which can record even a single particle of light. They then shot pulses of laser light at a wall that then - invisible to the human eye - bounce off objects around the corner and bounce back to the wall and to the detector.
Once the scan - which can take from two minutes to an hour, depending on conditions - is finished, the algorithm untangles the paths of the captured photons to construct an image. Currently the algorithm can achieve this in less than a second, and is so efficient it can run