Researchers perform non-line-of-sight ghost imaging with human vision
https://techxplore.com/news/2022-06-non-line-of-sight-ghost-imaging-human-vision.html

Researchers have shown that the computational imaging technique known as ghost imaging can be combined with human vision to image an object that can’t directly be seen by the person. The new work represents a step toward combining human intelligence with artificial intelligence.

“This is one of the first times that computational imaging has been performed by using the human visual system in a neurofeedback loop that adjusts the imaging process in real time,” said Faccio. “Although we could have used a standard detector in place of the human brain to detect the diffuse signals from the wall, we wanted to explore methods that might one day be used to augment human capabilities.”

The experimental setup used a projector to create light patterns on a cardboard cut-out that acted as the object being imaged. The transmitted light diffused onto a secondary white wall hidden from view by a dark wall. Thus, the observer could only see diffuse light reflected from the secondary white wall. Each light pattern was flickered at 6 Hz for two seconds, creating a signal in the observer’s visual cortex that was detected with a single-electrode electroencephalography (EEG) headset.

Those guys at Stanford must be watching a lot of James Bond movies. Their latest invention is a laser that can image an entire room through a keyhole. We imagine that will show up in a number of spy movies real soon now.

Keyhole Imaging | IEEE TCI 2021
https://www.computationalimaging.org/publications/keyhole-imaging/

Non-line-of-sight (NLOS) imaging and tracking is an emerging technology that allows the shape or position of objects around corners or behind diffusers to be recovered from transient, time-of-flight measurements. However, existing NLOS approaches require the imaging system to scan a large area on a visible surface, where the indirect light paths of hidden objects are sampled. In many applications, such as robotic vision or autonomous driving, optical access to a large scanning area may not be available, which severely limits the practicality of existing NLOS techniques. Here, we propose a new approach, dubbed keyhole imaging, that captures a sequence of transient measurements along a single optical path, for example, through a keyhole. Assuming that the hidden object of interest moves during the acquisition time, we effectively capture a series of time-resolved projections of the object’s shape from unknown viewpoints. We derive inverse methods based on expectation-maximization to recover the object’s shape and location using these measurements. Then, with the help of long exposure times and retroreflective tape, we demonstrate successful experimental results with a prototype keyhole imaging system.

Someday your self-driving car could react to hazards before you even see them, thanks to a laser-based imaging technology being developed by Stanford researchers that can peek around corners.