Category Archives: VR Hardware

Reviews of, and analyses of the capabilities of, VR-relevant hardware.

Optical Properties of Current VR HMDs

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With the first commercial version of the Oculus Rift (Rift CV1) now trickling out of warehouses, and Rift DK2, HTC Vive DK1, and Vive Pre already being in developers’ hands, it’s time for a more detailed comparison between these head-mounted displays (HMDs). In this article, I will look at these HMDs’ lenses and optics in the most objective way I can, using a calibrated fish-eye camera (see Figures 1, 2, and 3).

Figure 1: Picture from a fisheye camera, showing a checkerboard calibration target displayed on a 30" LCD monitor.

Figure 1: Picture from a fisheye camera, showing a checkerboard calibration target displayed on a 30″ LCD monitor.

Figure 2: Same picture as Figure 1, after rectification. The purple lines were drawn into the picture by hand to show the picture's linearity after rectification.

Figure 2: Same picture as Figure 1, after rectification. The purple lines were drawn into the picture by hand to show the picture’s linearity after rectification.

Figure 3: Rectified picture from Figure 2, re-projected into stereographic projection to simplify measuring angles.

Figure 3: Rectified picture from Figure 2, re-projected into stereographic projection to simplify measuring angles. Concentric purple circles indicate 5-degree increments away from the projection center point.

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Oculus Rift DK2’s tracking update rate

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I’ve been involved in some arguments about the inner workings of the Oculus Rift’s and HTC/Valve Vive’s tracking systems recently, and while I don’t want to get into any of that right now, I just did a little experiment.

The tracking update rate of the Oculus Rift DK2, meaning the rate at which Oculus’ tracking driver sends different position/orientation estimates to VR applications, is 1000 Hz. However, the time between updates is 2ms, meaning that the driver updates the position/orientation, and then updates it again immediately afterwards, 500 times per second.

This is not surprising at all, given my earlier observation that the DK2 samples its internal IMU at a rate of 1000 Hz, and sends data packets containing 2 IMU samples each to the host at a rate of 500 Hz. The tracking driver is then kind enough to process these samples individually, and pass updated tracking data to applications after it’s done processing each one. That second part is maybe a bit superfluous, but I’ll take it.

Here is a (very short excerpt of a) dump from the test application I wrote:

0.00199484: -0.0697729, -0.109664, -0.458555
6.645e-06 : -0.0698003, -0.110708, -0.458532
0.00199313: -0.069828 , -0.111758, -0.45851
6.012e-06 : -0.0698561, -0.112813, -0.458488
0.00200075: -0.0698847, -0.113875, -0.458466
6.649e-06 : -0.0699138, -0.114943, -0.458445
0.0019885 : -0.0699434, -0.116022, -0.458427
5.915e-06 : -0.0699734, -0.117106, -0.45841
0.0020142 : -0.070004 , -0.118196, -0.458393
5.791e-06 : -0.0700351, -0.119291, -0.458377
0.00199589: -0.0700668, -0.120392, -0.458361
6.719e-06 : -0.070099 , -0.121499, -0.458345
0.00197487: -0.0701317, -0.12261 , -0.45833
6.13e-06  : -0.0701651, -0.123727, -0.458314
0.00301248: -0.0701991, -0.124849, -0.458299
5.956e-06 : -0.0702338, -0.125975, -0.458284
0.00099399: -0.0702693, -0.127107, -0.458269
5.971e-06 : -0.0703054, -0.128243, -0.458253
0.0019938 : -0.0703423, -0.129384, -0.458238
5.938e-06 : -0.0703799, -0.130529, -0.458223
0.00200243: -0.0704184, -0.131679, -0.458207
7.434e-06 : -0.0704576, -0.132833, -0.458191
0.0019831 : -0.0704966, -0.133994, -0.458179
5.957e-06 : -0.0705364, -0.135159, -0.458166
0.00199577: -0.0705771, -0.136328, -0.458154
5.974e-06 : -0.0706185, -0.137501, -0.458141

The first column is the time interval between each row and the previous row, in seconds. The second to fourth rows are the reported (x, y, z) position of the headset.

I hope this puts the myth to rest that the DK2 only updates its tracking data when it receives a new frame from the tracking camera, which is 60 times per second, and confirms that the DK2’s tracking is based on dead reckoning with drift correction. Now, while it is possible that the commercial version of the Rift does things differently, I don’t see a reason why it should.

PS: If you look closely, you’ll notice an outlier in rows 15 and 17: the first interval is 3ms, and the second interval is only 1ms. One sample missed the 1000 Hz sample clock, and was delivered on the next update.

Lasers Are Not Magic

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“Can I make a full-field-of-view AR or VR display by directly shining lasers into my eyes?”

No.

Well, technically, you can, but not in the way you probably imagine if you asked that question. What you can’t do is mount some tiny laser emitter somewhere out of view, have it shine a laser directly into your pupil, and expect to get a virtual image covering your entire field of view (see Figure 1). Light, and your eyes, don’t work that way.

Figure 1: A magical retinal display using a tiny laser emitter somewhere off to the side of each eye. This doesn't work in reality.

Figure 1: A magical retinal display using a tiny laser emitter somewhere off to the side of each eye. This doesn’t work in reality. If a single beam of light entering the eye could be split up to illuminate large parts of the retina, real-world vision would not work.

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HoloLens and Holograms

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Today Microsoft announced a release window (first quarter 2016) and price (USD 3,000) for HoloLens developer kits, so suddenly HoloLens, and discussion thereof, is all over the Internet again.

Figure 1: Microsoft’s HoloLens.

I’ve already talked about HoloLens ad nauseam, but I found myself several times today trying to explain where (I think) the “Holo” in HoloLens comes from, and what HoloLens has to do with actual, real, honest-to-goodness holograms. Continue reading →

Blast from the Past

Aside

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I just stumbled upon an interview I did almost four years ago for Greg Borenstein’s book “Making Things See: 3D vision with Kinect, Processing, Arduino, and MakerBot.”

The relevant part of the book, starting on page 29, is available online via Google Books. It’s cringeworthy because I’m talking about basically the same things I’m talking about these days, but had a hard time as this was before the current VR renaissance. I probably failed entirely to get my main points across to an audience that had never experienced VR, and had never considered it anything but an old and busted thing from the ’90s.

Zero-latency Rendering

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I finally managed to get the Oculus Rift DK2 fully supported in my Vrui VR toolkit, and while there are still some serious issues, such as getting the lens distortion formulas and internal HMD geometry exactly right, I’ve already noticed something really neat.

I have a bunch of graphically simple applications that run at ridiculous frame rates (some get several thousand fps on an Nvidia GeForce 770 GTX), and with some new rendering configuration options in Vrui 4.0 I can disable vsync, and render directly into the display window’s front buffer. In other words, I can let these applications “race the beam.”

There are two main results of disabling vsync and rendering into the front buffer: For one, the CPU and graphics card get really hot (so this is not something you want to do this naively). But second, let’s assume that some application can render 1,000 fps. This means, every millisecond, a new complete video frame is rendered into video scan-out memory, where it gets picked up by the video controller and sent across the video link immediately. In other words, almost every line of the Rift’s display gets a “fresh” image, based on most up-to-date tracking data, and flashes this image to the user’s retina without further delay. Or in other words, total motion-to-photon latency for the entire screen is now down to around 1ms. And the result of that is by far the most solid VR I’ve ever seen.

Not entirely useful, but pretty cool nonetheless.

HoloLens and Field of View in Augmented Reality

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Since Microsoft’s Build 2015 conference, and increasingly since Microsoft’s showing at E3, everybody (including me) has been talking about HoloLens, and its limited field of view (FoV) has been a contentious topic. The main points being argued (fought) about are:

  1. What exactly is the HoloLens’ FoV?
  2. Why is it as big (or small) as it is, and will it improve for the released product?
  3. How does the size of the FoV affect the HoloLens’ usability and effectiveness?
  4. Were Microsoft’s released videos and live footage of stage demos misleading?
  5. How can one visualize the HoloLens’ FoV in order to give people who have not tried it an idea what it’s like?

Measuring Field of View

Initially, there was little agreement among those who experienced HoloLens regarding its field of view. That’s probably due to two reasons: one, it’s actually quite difficult to measure the FoV of a headmounted display; and two, nobody was allowed to bring any tools or devices into the demonstration rooms. In principle, to measure see-through FoV, one has to hold some object, say a ruler, at a known distance from one’s eyes, and then mark down where the apparent left and right edges of the display area fall on the object. Knowing the distance X between the left/right markers and the distance Y between the eyes and the object, FoV is calculated via simple trigonometry: FoV = 2×tan-1(X / (Y×2)) (see Figure 1).

Figure 1: Calculating field of view by measuring the horizontal extent of the apparent screen area at a known distance from the eyes. (In this diagram, FoV is 2×tan-1(6″ / (6″×2)) = 53.13°.)

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On the road for VR: Redwood City, California

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Last Friday I made a trek down to the San Francisco peninsula, to visit and chat with a couple of other VR folks: Cyberith, SVVR, and AltspaceVR. In the process, I also had the chance to try a couple of VR devices I hadn’t seen before.

Cyberith Virtualizer

Virtual locomotion, and its nasty side effect, simulator sickness, are a pretty persistent problem and timely topic with the arrival of consumer VR just around the corner. Many enthusiasts want to use VR to explore large virtual worlds, as in taking a stroll through the frozen tundra of Skyrim or the irradiated wasteland of Fallout, but as it turns out, that’s one of the hardest things to do right in VR.

Figure 1: Cyberith Virtualizer, driven by an experienced user (Tuncay Cakmak). Yes, you can jump and run, with some practice.

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On the Road for VR: Augmented World Expo 2015, Part I: VR

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I attended the Augmented World Expo (AWE) once before, in 2013 when I took along an Augmented Reality Sandbox. This time, AWE partnered with UploadVR to include a significant VR subsection. I’m going to split my coverage, focusing on that VR component here, while covering the AR offering in another post.

eMagin 2k×2k VR HMD

eMagin’s (yet to be named) new head-mounted display was the primary reason I went to AWE in the first place. I had seen it announced here and there, but I was skeptical it would be able to provide the advertised field of view of 80°×80°. Unlike Oculus Rift, HTC/Valve Vive, or other post-renaissance HMDs, eMagin’s is based on OLED  microdisplays (unsurprisingly, with microdisplay manufacture being eMagin’s core business). Previous microdisplay-based HMDs, including eMagin’s own Z800 3DVisor, were very limited in the FoV department, usually topping out around 40°. Magnifying a display that measures around 1cm2 to a large solid angle requires much more complex optics than doing the same for a screen that’s several inches across.

Figure 1: eMagin’s unnamed 2k x 2k, 80×80 degree FoV, VR HMD with flip-up optics.

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On the road for VR: Silicon Valley Virtual Reality Conference & Expo

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Yesterday, I attended the second annual Silicon Valley Virtual Reality Conference & Expo in San Jose’s convention center. This year’s event was more than three times bigger than last year’s, with around 1,400 attendees and a large number of exhibitors.

Unfortunately, I did not have as much time as I would have liked to visit and try all the exhibits. There was a printing problem at the registration desk in the morning, and as a result the keynote and first panel were pushed back by 45 minutes, overlapping the expo time; additionally, I had to spend some time preparing for and participating in my own panel on “VR Input” from 3pm-4pm.

The panel was great: we had Richard Marks from Sony (Playstation Move, Project Morpheus), Danny Woodall from Sixense (STEM), Yasser Malaika from Valve (HTC Vive, Lighthouse), Tristan Dai from Noitom (Perception Neuron), and Jason Jerald as moderator. There was lively discussion of questions posed by Jason and the audience. Here’s a recording of the entire panel:

One correction: when I said I had been following Tactical Haptics‘ progress for 2.5 years, I meant to say 1.5 years, since the first SVVR meet-up I attended. Brainfart. Continue reading →