They are buying them to make dash cams for self driving cars is my guess...
That tech in dash-cam video is priceless
That tech in dash-cam video is priceless
With dash-cam video you can just chose a fixed hyperfocal distance and have everything in good focus.
You certainly don't need creative DoP and bokeh...
You can also see past occlusions, something not possible with stereo.
With a larger and more distributed camera array, cameras could be pointed everywhere so that every point in the field has a certain level of coverage.
Using stereoscopic as an example, you can synthesize a 2d image with the center being between the two sensors. The further apart you place the sensors, up to some limit, the more you can "rotate" the scene. But you lose a lot of data when the viewing angles become too extreme. A light field image can be used for the same effect, but because it's one sensor your ability to rotate the scene will be constrained (as if you had two sensors very close together).
Apparently the examples I saw years ago on Lytro's site aren't available anymore. It was a neat effect with their initial camera, I imagine higher quality cameras could do much more.
A neat thing with light field sensors versus stereoscopic is that you have far more freedom in how you move around the scene. With two sensors you can only move "left and right" or "up and down". With light field data and one sensor you can move in any direction.
(I spent a lot of time reading about light field stuffs back when Lytro was first announced, I was also tangentially connected to a synthetic aperture radar project so it piqued a lot of my curiosity at the time. I haven't kept up with the state-of-the-art since then, though.)
I think it worked by making a point cloud that fits the camera observations.
Obstruction is not a big issue in that use case, but if there was obstruction, the system could choose to ignore pixels that were obstructed when constructing the image.
Light field sensors could greatly aid self-driving vehicles as a significant improvement over standard cameras and stereoscopic configurations for object detection. It's not as good as Lidar in some ways, but it's much less expensive and offers some of the same kinds of data (which means greater portability of algorithms or techniques between the two sensor types). And since cars need to see the same visual cues humans do, we need cameras anyways (for reading signs and road directions, lane detection, etc.) so using a light field sensor could offer a twofer. Improved object detection plus the ability to do visual detection we already need.
segmentation of foreground/background, becomes much simpler.