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

Piergiorgio Caramazza, Alessandro Boccolini, Daniel Buschek, Matthias Hullin, Catherine Higham, Robert Henderson, Roderick Murray-Smith, Daniele Faccio

Research output: Contribution to journalArticlepeer-review

Abstract

Light scattered from multiple surfaces can be used to retrieve information of hidden environments. However, full threedimensional
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). Artificial neural networks applied to
specific computational imaging problems can therefore enable novel imaging capabilities with hugely simplified hardware and
processing times.
Original languageEnglish
Article number11945
Number of pages12
JournalScientific Reports
Issue number8
DOIs
Publication statusPublished - 9 Aug 2018

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