Machine Vision Gets Boost in Rain and Fog
RandomFactor writes:
Researchers have developed a system that improves machine vision through obscuring clouds and fog.
Referred to as 'confocal diffuse tomography',
[t]he newly developed system works via an algorithm that measures the movement of individual light particles or photons, as fired in fast pulses from a laser, and uses them to reconstruct objects that are obscured or hidden from the human eye.
What makes the technique extra special is the way that it can reconstruct light that's been scattered and bounced around by the barrier in the way.
In experiments, the laser sight was able to see objects hidden behind a 1-inch layer of foam.
Existing techniques for machine viewing in similar scenarios have major drawbacks. Some only work at microscopic scales, some require access to both sides of the diffusing medium, and others require prior knowledge of the object being viewed. The most comparable method relies on excluding scattered photons by time-gating of ballistic (non-scattered) photons and using them to construct images, however this approach degrades rapidly for greater propagation distances and more highly scattering media as ballistic photons drop towards zero.
Confocal diffuse tomography is different in that it reconstructs images from the scattered photons "modeling and inverting the scattering of photons that travel through a thick diffuser." It has a variety of potential applications including self driving vehicles whose LiDAR struggles in rain and fog, robotic vision, and viewing planetary surfaces through cloud cover.
The researchers caution that the approach is currently slow and requires significant optimization, but they are "excited to push [the approach] further."
Journal Reference:
David B. Lindell, Gordon Wetzstein. Three-dimensional imaging through scattering media based on confocal diffuse tomography [open], Nature Communications (DOI: 10.1038/s41467-020-18346-3)
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