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

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

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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 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
JournalScientific Reports
Volume8
DOIs
Publication statusPublished - 9 Aug 2018

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    Caramazza, P., Boccolini, A., Buschek, D., Hullin, M., Higham, C. F., Henderson, R., Murray-Smith, R., & Faccio, D. (2018). Neural network identification of people hidden from view with a single-pixel, single-photon detector. Scientific Reports, 8, [11945]. https://doi.org/10.1038/s41598-018-30390-0