Computational imaging with the human brain
This work presents a novel approach to augmented human computation, potentially extending the sensing range of human vision and offering new methods for studying neurophysics, though it appears incremental in its current experimental demonstration.
The paper tackles the problem of computational imaging by blending the human visual system with external silicon processing via brain-computer interfaces, demonstrating ghost imaging of a hidden scene with a projection pattern carving technique that uses real-time brain feedback to improve efficiency and resolution.
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.