Friday, August 22, 2014

Using basic statistical analysis to discover whether or not the Oculus Rift headset is being worn

As we were getting ready for our talk next week at PAX Dev 2014, entitled "Pitfalls & Perils of VR Development: How to Avoid Them", an interesting question came up: how can you tell if the Rift is actually on the user's head, instead of on their desk?  It's a pretty common (and annoying) scenario right now--you double-click to launch a cool new game, and immediately you can hear intro music and cutscene dialog but the Rift's still on a table.  I hate feeling like, ack!, I have to scramble to get the Rift on my face to see the intro.

Valve's SteamVR will help with this a lot, I expect; if I launch a game when I'm already wearing the Rift, there'll be no jarring switch.  But I'm leery--half the Rift demos I download today start by popping up a Unity dialog on my desktop before they switch to fullscreen VR, and that's going to be an even worse experience if I'm using Steam.

So I was mulling over how to figure out programmatically whether or not the Rift is on the user's head.  I figure that we can't just look at the position data from the tracker camera, because "camera can see Rift" isn't a firm indicator of "Rift is being used".  (Maybe the Rift is sitting on my desk, in view of the camera.)  Instead, we need to look at the noise of its position.

I recorded the eye pose at each frame, taking an average of all eye poses recorded every tenth of a second.  At 60FPS that's about six positions per decisecond.  The Rift's positional sensors are pretty freaking sensitive; when the Rift is sitting on my desk, the difference in position from one decisecond to the next from ambient vibration is on the order of a hundredth of a millimeter.  Pick it up, though, and those differences spike.

I plotted the standard deviation of the Rift's position, in a rolling window of ten samples for the past second, versus time:

This is a graph of log(standard deviation(average change in position per decisecond)) over time.  The units on the left are in log scale.  I found that when the Rift was inert on my desk, casual vibration kept log(σ) < -10.5; as I picked it up log(σ) spiked, and then while worn would generally hover between -4.5 and -10.5.  When the Rift was being put on or taken off, log(σ) climbed as high as -2, but only very briefly.

I found that distinguishing between Rift that was being put on or lifted off from a Rift that was being worn normally was pretty hard with this method, but that the distinction between "not in human hands at all" and "in use" was clear.  So this demonstrates a method for programmatically determining whether the Rift is in active use or not.  I hope it's useful.

Sample code was written in Java, and is available on the book's github repo.  (File "".)

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