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

Autor:	Caramazza, Piergiorgio, Boccolini, Alessandro, Buschek, Daniel, Hullin, Matthias, Higham, Catherine, Henderson, Robert, Murray-Smith, Roderick, Faccio, Daniele
Rok vydání:	2017
Předmět:	Computer Science - Computer Vision and Pattern Recognition Physics - Optics
Druh dokumentu:	Working Paper
Popis:	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
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1709.07244 Zobrazit plný text záznamu View this record from Arxiv