Brain-computer interfaces (BCIs) are enabling a range of new possibilities
and routes for augmenting human capability. Here, we propose BCIs as a route
towards forms of computation, i.e. computational imaging, that blend the brain
with external silicon processing. We demonstrate ghost imaging of a hidden
scene using the human visual system that is combined with an adaptive
computational imaging scheme. This is achieved through a projection pattern
`carving' technique that relies on real-time feedback from the brain to modify
patterns at the light projector, thus enabling more efficient and higher
resolution imaging. This brain-computer connectivity demonstrates a form of
augmented human computation that could in the future extend the sensing range
of human vision and provide new approaches to the study of the neurophysics of
human perception. As an example, we illustrate a simple experiment whereby
image reconstruction quality is affected by simultaneous conscious processing
and readout of the perceived light intensities.
%0 Generic
%1 wang2022computational
%A Wang, Gao
%A Faccio, Daniele
%D 2022
%K imaging
%T Computational imaging with the human brain
%U http://arxiv.org/abs/2210.03400
%X Brain-computer interfaces (BCIs) are enabling a range of new possibilities
and routes for augmenting human capability. Here, we propose BCIs as a route
towards forms of computation, i.e. computational imaging, that blend the brain
with external silicon processing. We demonstrate ghost imaging of a hidden
scene using the human visual system that is combined with an adaptive
computational imaging scheme. This is achieved through a projection pattern
`carving' technique that relies on real-time feedback from the brain to modify
patterns at the light projector, thus enabling more efficient and higher
resolution imaging. This brain-computer connectivity demonstrates a form of
augmented human computation that could in the future extend the sensing range
of human vision and provide new approaches to the study of the neurophysics of
human perception. As an example, we illustrate a simple experiment whereby
image reconstruction quality is affected by simultaneous conscious processing
and readout of the perceived light intensities.
@misc{wang2022computational,
abstract = {Brain-computer interfaces (BCIs) are enabling a range of new possibilities
and routes for augmenting human capability. Here, we propose BCIs as a route
towards forms of computation, i.e. computational imaging, that blend the brain
with external silicon processing. We demonstrate ghost imaging of a hidden
scene using the human visual system that is combined with an adaptive
computational imaging scheme. This is achieved through a projection pattern
`carving' technique that relies on real-time feedback from the brain to modify
patterns at the light projector, thus enabling more efficient and higher
resolution imaging. This brain-computer connectivity demonstrates a form of
augmented human computation that could in the future extend the sensing range
of human vision and provide new approaches to the study of the neurophysics of
human perception. As an example, we illustrate a simple experiment whereby
image reconstruction quality is affected by simultaneous conscious processing
and readout of the perceived light intensities.},
added-at = {2023-06-07T05:17:00.000+0200},
author = {Wang, Gao and Faccio, Daniele},
biburl = {https://www.bibsonomy.org/bibtex/20bd8af9e19a5c35cff3b05474ccba000/lucyday},
description = {Computational imaging with the human brain},
interhash = {b4753f3ef1d890697f7c1868d7cc9368},
intrahash = {0bd8af9e19a5c35cff3b05474ccba000},
keywords = {imaging},
note = {cite arxiv:2210.03400},
timestamp = {2023-06-07T05:17:00.000+0200},
title = {Computational imaging with the human brain},
url = {http://arxiv.org/abs/2210.03400},
year = 2022
}