Deep Learning Enables Real-Time 3D Holograms On a Smartphone

An anonymous reader quotes a report from IEEE Spectrum:

Now researchers at MIT have developed a new way to produce holograms nearly instantly – a deep-learning based method so efficient, it can generate holograms on a laptop in a blink of an eye. They detailed their findings this week, which were funded in part by Sony, online in the journal Nature. Using physics simulations for computer-generated holography involves calculating the appearance of many chunks of a hologram and then combining them to get the final hologram. Using lookup tables is like memorizing a set of frequently used chunks of hologram, but this sacrifices accuracy and still requires the combination step.
The researchers first built a custom database of 4,000 computer-generated images, which each included color and depth information for each pixel. This database also included a 3D hologram corresponding to each image. Using this data, the convolutional neural network learned how to calculate how best to generate holograms from the images. It could then produce new holograms from images with depth information, which is provided with typical computer-generated images and can be calculated from a multi-camera setup or from lidar sensors, both of which are standard on some new iPhones. The new system requires less than 620 kilobytes of memory, and can generate 60 color 3D holograms per second with a resolution of 1,920 by 1,080 pixels on a single consumer-grade GPU. The researchers could run it an iPhone 11 Pro at a rate of 1.1 holograms per second and on a Google Edge TPU at a rate of 2 holograms per second, suggesting it could one day generate holograms in real-time on future virtual-reality (VR) and augmented-reality (AR) mobile headsets.

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