Neural network identification of people hidden from view with a single-pixel, single-photon detector
Computer Vision and Pattern Recognition
2017-09-22 v1 Optics
Abstract
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 an 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). Artificial neural networks applied to specific computational imaging problems can therefore enable novel imaging capabilities with hugely simplified hardware and processing times
Keywords
Cite
@article{arxiv.1709.07244,
title = {Neural network identification of people hidden from view with a single-pixel, single-photon detector},
author = {Piergiorgio Caramazza and Alessandro Boccolini and Daniel Buschek and Matthias Hullin and Catherine Higham and Robert Henderson and Roderick Murray-Smith and Daniele Faccio},
journal= {arXiv preprint arXiv:1709.07244},
year = {2017}
}