Revolutionary Technology Can See Around Corners 'Like Magic'

Researchers from Stanford University are developing a new technique that can effectively see around corners by harnessing the power of lasers.

The new technology has a variety of applications. It could be used in driverless cars to avoid collisions with unseen hazards or in aerial vehicles to see through foliage. It could even be used during search and rescue operations to help identify people blocked from view by walls or rubble.

"It sounds like magic, but the idea of non-line-of-sight imaging is actually feasible," Gordon Wetzstein, assistant professor of electrical engineering and senior author of a new paper describing the work—published in the journal Nature–said in a statement.

The technique involves a laser and an incredibly sensitive piece of equipment that can detect even a single particle of light—known as a photon.

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The laser is shone at a wall where the light reflects off, hits objects around the corner and returns to be detected by the sensing equipment, a process invisible to the human eye.

Using the data from the captured photons, an algorithm then calculates the path they took to reach the detector in order to produce an image of what is behind the corner.

The process of creating the image is so efficient that it can run on a regular laptop. However, the initial laser scan currently takes between two minutes and an hour depending on the conditions—including the reflectivity of the object—something the researchers are looking to make instantaneous.

Illustration of the non-line-of-sight imaging system. Stanford Computational Imaging Lab

The technology was particularly efficient at detecting reflective objects. However, researchers say some aspects will have to be improved before it is ready for use. For example, it will need to work better in brighter conditions and detecting objects that are in motion.

While this isn't the first technology in development that's designed to see objects around corners, the new algorithm is far more efficient and effective at producing an image than previous attempts, researchers said.

"This is a big step forward for our field that will hopefully benefit all of us," said Wetzstein. "In the future, we want to make it even more practical in the wild.'"

David Lindell, a Stanford graduate student in the Computational Imaging Lab and co-author of the paper, added: "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. I think the big impact of this method is how computationally efficient it is."