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upstart writes in with an IRC submission for Bytram:

Deep learning enables real-time imaging around corners:

Researchers have harnessed the power of a type of artificial intelligence known as deep learning to create a new laser-based system that can image around corners in real time. With further development, the system might let self-driving cars "look" around parked cars or busy intersections to see hazards or pedestrians. It could also be installed on satellites and spacecraft for tasks such as capturing images inside a cave on an asteroid.

"Compared to other approaches, our non-line-of-sight imaging system provides uniquely high resolutions and imaging speeds," said research team leader Christopher A. Metzler from Stanford University and Rice University. "These attributes enable applications that wouldn't otherwise be possible, such as reading the license plate of a hidden car as it is driving or reading a badge worn by someone walking on the other side of a corner."

[...] The new imaging system uses a commercially available camera sensor and a powerful, but otherwise standard, laser source that is similar to the one found in a laser pointer. The laser beam bounces off a visible wall onto the hidden object and then back onto the wall, creating an interference pattern known as a speckle pattern that encodes the shape of the hidden object.

Reconstructing the hidden object from the speckle pattern requires solving a challenging computational problem. Short exposure times are necessary for real-time imaging but produce too much noise for existing algorithms to work. To solve this problem, the researchers turned to deep learning.

"Compared to other approaches for non-line-of-sight imaging, our deep learning algorithm is far more robust to noise and thus can operate with much shorter exposure times," said co-author Prasanna Rangarajan from Southern Methodist University. "By accurately characterizing the noise, we were able to synthesize data to train the algorithm to solve the reconstruction problem using deep learning without having to capture costly experimental training data."

More information: Chris Metzler et al, Deep-Inverse Correlography: Towards Real-Time High-Resolution Non-Line-of-Sight Imaging, Optica (2019). DOI: 10.1364/OPTICA.374026

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