Real-Time Scene Monitoring for Deaf-Blind People.

It is estimated that at least 15 million people worldwide live with severe deaf-blindness, with many more experiencing varying degrees of deaf-blindness. The existing options of assistance are mostly limited to walking canes, guide dogs and human care. We propose a wearable device which harnesses a multi-antenna mmWave radar transceiver and a haptic feedback array for real time detection of a person moving within a scene.

Transmission of natural scene images through a multimode fibre.

The optical transport of images through a multimode fibre remains an outstanding challenge with applications ranging from optical communications to neuro-imaging. State of the art approaches either involve measurement and control of the full complex field transmitted through the fibre or, more recently, training of artificial neural networks that however, are typically limited to image classes belong to the same class as the training data set. Here we implement a method that statistically reconstructs the inverse transformation matrix for the fibre.

Neural network identification of people hidden from view with a single-pixel, single-photon detector.

Light scattered from multiple surfaces can be used to retrieve information of hidden environments. However, full three-dimensional retrieval of an object hidden from view by a wall has only been achieved with scanning systems and requires intensive computational processing of the retrieved data. Here we use a non-scanning, single-photon single-pixel detector in combination with a deep convolutional artificial neural network: this allows us to locate the position and to also simultaneously provide the actual identity of a hidden person, chosen from a database of people (N = 3).

Enhancing the recovery of a temporal sequence of images using joint deconvolution.

In this work, we address the reconstruction of spatial patterns that are encoded in light fields associated with a series of light pulses emitted by a laser source and imaged using photon-counting cameras, with an intrinsic response significantly longer than the pulse delay. Adopting a Bayesian approach, we propose and demonstrate experimentally a novel joint temporal deconvolution algorithm taking advantage of the fact that single pulses are observed simultaneously by different pixels. Using an intensified CCD camera with a 1000-ps gate, stepped with 10-ps increments, we show the ability to resolve images that are separated by a 10-ps delay, four time better compared to standard deconvolution techniques.

Intrinsic Negative Mass from Nonlinearity.

We propose and provide experimental evidence of a mechanism able to support negative intrinsic effective mass. The idea is to use a shape-sensitive nonlinearity to change the sign of the mass in the leading linear propagation equation. Intrinsic negative-mass dynamics is reported for light beams in a ferroelectric crystal substrate, where the diffusive photorefractive nonlinearity leads to a negative-mass Schrödinger equation.