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Comment by blackguardx | Hacker News Reader

A light source built into the camera is modulated in time. The camera uses this to infer depth. When the modulation is synced up right, the camera can see the light wave "travel" as it illuminates close objects first and then farther ones over successive frames. The camera isn't actually fast enough to capture the light wave traveling, but the timing between the shutter and the light source is shifted by nanoseconds each frame to accomplish this.

They can have problems operating outside because it is hard to make a lightsource brighter than the sun.

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That's an older form of ranging. It's easier to do than pulse ranging, but you have to outshine ambient light at the color being used full time. The Swiss Ranger [1] is a good example of such a system. It's indoor only and short range. With a pulse system, you only have to outshine ambient light for a nanosecond, which is quite possible in sunlight.

I've been expecting good, cheap non-scanning laser distance imagers for a decade. In 2003, I went down to Advanced Scientific Concepts in Santa Barbara and saw the first prototype, as a collection of parts on an optical bench. Today ASC makes good units [2], but they cost about $100K. DoD and Space-X buy them. There's one on the Dragon spacecraft, for docking. That technology isn't inherently expensive, but requires custom semiconductors produced with non-standard processes such as InGaAs. Those cost too much in small volumes. There's been progress in coming up with designs that can be made in standard CMOS fabs.[3] When that hits production, laser rangefinders will cost like CMOS cameras.

[1] http://www.adept.net.au/cameras/Mesa/SR4000.shtml [2] http://www.advancedscientificconcepts.com/products/overview.... [3] https://books.google.com/books?id=Op6NCwAAQBAJ&lpg=PA64

Hey, 3D vision system amateur here, but very interested to learn more!

Can anybody point me to some literature or reference materials about attempts to combine the inputs from multiple techniques simultaneously?

E.g. a device with stereo conventional cameras and infrared cameras & emitters which compares the resulting model from each input source/technique and actively re-adjusts final depth estimate?

Is "sensor fusion" the right jargon to use in this context?

Or, even crazier, a control system which actively jitters the camera's pose to gain more information for points in the depth map with lower confidence scores / conflicting estimates?

But maybe such a setup is overly complex and yields minimal gains in mixed indoor & outdoor scenarios?

We have a setup that combines ToF, structured light and multiple colour cameras to reconstruct hands from the elbow down. Short version: it's a massive pain in the ass. In fact the setup really only works because we have a preconceived motion model (particular hand gestures) and have carefully arranged the scene to avoid interference. I'm unaware of a general solution where you can just throw more cameras in and get better scene data.

One neat thing though you might want to look at: if all you have is structured light (ie Kinect v1) you can simply attach a vibrating motor to each emitter/receiver to avoid a lot of interference per [0]

[0] https://wwwx.cs.unc.edu/~maimone/media/kinect_VR_2012.pdf

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