Category Archives: VR Methods

Discussions of methods, interaction metaphors, designs, architectures, paradigms, used in immersive 3D graphics.

A New AR Sandbox Support Forum

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Apparently, the AR Sandbox is still a thing and going strong after ten years, with over 850 registered installations world-wide according to the AR Sandbox World Map. There was a lull in new installations and community activity during the initial COVID-19 lockdowns, but things are picking up again, and with that I am seeing an increasing amount of requests for help arriving in my personal email.

An AR Sandbox.

The old AR Sandbox support forum, which was quite active and significantly reduced my support load, not only by allowing me to answer common questions only once instead of dozens of times, but also by community members directly helping each other, unfortunately went down due to hardware problems a good while ago, and there is currently no avenue of getting it back up.

So I decided to create a new AR Sandbox support forum on this here web site, as a hopefully temporary replacement. I was not able to move over any of the old forum content due to not having access to the original database files, which is a major pity because there was a ton of helpful stuff on there. I am hoping that the new forum will accumulate its own set of helpful stuff quickly, and if/when I migrate the forum to a permanent location, I will be able to move all content because I have full access to this web site’s code and database. So here’s hoping.

This is the first forum on this web site, so I hope that things will work right from the start; if not, we’ll figure out how to fix it. Please be patient.

And as a quick reminder: These are the only official AR Sandbox installation instructions. Accept no substitutes.

Is TCP really that slow?

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I’m still working on Vrui’s second-generation collaboration / tele-presence infrastructure (which is coming along nicely, thankyouverymuch), and I also recently started working with another group of researchers who are trying to achieve similar goals, but have some issues with their own home-grown network system, which is based on Open Sound Control (OSC). I did some background research on OSC this morning, and ran into several instances of an old pet peeve of mine: the relative performance of UDP vs TCP. Actually, I was trying to find out whether OSC communicates over UDP or TCP, and whether there is a way to choose between those at run-time, but most sources that turned up were about performance (it turns out OSC simply doesn’t do TCP).

Here are some quotes from one article I found: “I was initially hoping to use UDP because latency is important…” “I haven’t been able to fully test using TCP yet, but I’m hopeful that the trade-off in latency won’t be too bad.”

Here are quotes from another article: “UDP has it’s [sic] uses. It’s relatively fast (compared with TCP/IP).” “TCP/IP would be a poor substitute [for UDP], with it’s [sic] latency and error-checking and resend-on-fail…” “[UDP] can be broadcast across an entire network easily.” “Repeat that for multiple players sharing a game, and you’ve got a pretty slow, unresponsive game. Compared to TCP/IP then UDP is fast.” “For UDP’s strengths as a high-volume, high-speed transport layer…” “Sending data via TCP/IP has an ‘overhead’ but at least you know your data has reached its destination.” “… if the response time [over TCP] was as much as a few hundred milliseconds, the end result would be no different!”

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Quantitative Comparison of VR Headset Fields of View

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Although I’ve taken many through-the-lens pictures of several common VR headsets with a calibrated wide-angle camera, until recently I was still struggling how to compare the resulting fields of view (FoV) quantitatively, how to put them in context, and how to visualize them appropriately. When trying to answer questions like “which VR headset has a bigger FoV?” or “by how much is headset A’s FoV bigger than headset B’s?” or “how does headset C’s FoV compare to the field of vision of the naked human eye?”, the basic question is: how does one even measure field of view, in a way that is fair and allows comparison across a wide range of possible sizes. Does one report a single angle, and how does one measure it? Across the “diagonal” of the field of view? What if the field of view is not a rectangle? Does one report a pair of angles, say horizontal⨉vertical? Again, what if the field of view is not a rectangle?

Then, if FoV is measured either as a single angle or a pair of angles, how does one compare different FoVs fairly? If one headset has 100° FoV, and another has 110°, does the latter show 10% more of a virtual 3D environment? What if one has 100°⨉100° and another has 110°⨉110°, does the latter show 21% more?

To find a reasonable answer, let’s go back to the basics: what does FoV actually measure? The general idea is that FoV measures how much of a virtual 3D environment a user can see at any given instant, meaning, without moving their head. A larger FoV value should mean that a user can see more, and, ideally, an FoV value that is twice as large should mean that a user can see twice as much.

Now, what does it mean that “something can be seen?” We can see something if light from that something reaches our eye, enters the eye through the cornea, pupil, and lens, and finally hits the retina. In principle, light travels towards our eyes from all possible directions, but only some of those directions end up on the retina due to various obstructions (we can’t see behind our heads, for example). So a reasonable measure of field of view (for one eye) would be the total number of different 3D directions from which light reaches that eye’s retina. The problem is that there is an infinite number of different directions from which light can arrive, so simple counting does not work.

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Visual Simulation of the Resolution of VR Headsets

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While I was writing up my article on the PlayStation VR headset’s optical properties yesterday, and specifically when I made the example images for the sub-section about sub-pixel layout comparing RGB Stripe and PenTile RGBG displays, it occurred to me that I could use those images to create a rough and simple simulator to visually evaluate the differences between VR headsets that have different resolutions and sub-pixel layouts.

The basic idea is straightforward: Take a test image that has some pixel count, for example WxH=640×360 as the initial low-resolution full-RGB picture seen in Figure 1. If you then blow up that image to fill a monitor that has the same aspect ratio (16:9) and some diagonal size D, the resolution of that image in terms of pixels per degree depends both on D and the viewer’s distance from the monitor Y: the larger the ratio Y/D, the higher is the image’s resolution as seen by the viewer. In detail, the formula for distance Y to achieve a desired resolution R in pixels/° is:

Y = (D / sqrt(W*W + H*H))/(2*tan(1/(2*R)))

where W and H are in pixel units, R is in pixels/°, and D is in some arbitrary length unit (inch, meter, parsec,…). Y will end up being in the same unit as D.

If a viewer then positions one of their eyes at a distance of Y from the center of the monitor and closes the other one, the resolution of the image on the monitor will be R. In other words, if R is the known resolution of some VR headset, the image on the monitor will look the same resolution as that VR headset.

There is one caveat: when looking at a flat monitor, the resolution of the displayed image increases away from the monitor’s center, while in a VR headset, the resolution generally decreases away from the center direction (see this article for reference). Meaning, for a correct evaluation, the viewer has to focus on the area in the center of the monitor. Unfortunately there is no easy way to simulate resolution drop-off using a flat monitor, at least not while also simulating sub-pixel layout.

Simulation Procedure

Here’s what you need to do: Continue reading →

Field of View and Resolution of the PlayStation VR Headset

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It has been a very long time since I did the original optical measurement of then-current VR headsets. I have owned a PlayStation VR headset (PSVR from now on) for almost a year now, and I finally got around to measuring its optical properties in the same way. I also developed a new camera calibration algorithm (that’s a topic for another post), meaning I am even more confident in my measurements now than I was then.

One approach to measuring the optical properties of a VR headset, which includes measuring its field of view, its resolution in pixels/°, and its lens distortion correction profile, is to take a series of pictures of the headset’s screen(s) through its lenses using a calibrated wide-angle camera. In this context, a calibrated camera is one where each image pixel’s horizontal and vertical angles away from the optical axis are precisely known.

If one then displays a test pattern that lets one identify a particular pixel on the screen, one can measure the viewer-relative angular position of that pixel in the camera image, which is all the information needed to generate the projection matrices and lens distortion correction formulas that are essential to high-quality VR rendering.

Without further ado, here is a series of 7 images taken with the camera lens at increasing distances from the headset’s right lens (Figures 1-7, and yes, I forgot to clean my PSVR’s lens). The camera was carefully positioned and aligned such that it was sliding back along the lens’s optical axis, and looking straight ahead. The first image was captured with an eye relief value of 0mm, meaning that the camera lens was touching the headset’s lens. The rest of the images were captured with increasing eye relief values, or lens-lens distances, of 5mm, 10mm, 15mm, 20mm, 25mm, and 30mm: Continue reading →

KeckCAVES On Mars, pt. Oh-I-lost-count

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Last weekend, we had yet another professional film crew visiting us to shoot video about our involvement in NASA’s still on-going Mars Science Laboratory (MSL, aka Curiosity rover) mission. This time, they were here to film parts of an upcoming 90-minute special about Mars exploration for the National Geographic TV channel. Like last time, the “star” of the show was Dawn Sumner, faculty in the UC Davis Department of Earth and Planetary Sciences, one of the founding members of KeckCAVES, and member of the MSL science team.

Unlike last time, we did not film in the KeckCAVES facility itself (due to the demise of our CAVE), but in the UC Davis ModLab. ModLab is part of an entirely different unit — UC Davis’s Digital Humanities initiative — but we are working closely with them on VR development, they have a nice VR environment consisting of two HTC Vive headsets and a large 4.2m x 2.4m screen with a ceiling-mounted ultra-short throw projector (see Figure 1), their VR hardware is running our VR software, and they were kind enough to let us use their space.

Figure 1: Preparation for filming in UC Davis’s ModLab, showing its 4.2m x 2.4m front-projected screen and ceiling-mounted ultra-short throw projector, and two Lighthouse base stations.

The fundamental idea here was to use several 3D models, created or reconstructed from real data sent back either by satellites orbiting Mars or by the Curiosity rover itself, as backdrops to let Dawn talk about the goals and results of the MSL mission, and her personal involvement in it. Figure 1 shows a backdrop in the real sense of the word, i.e., a 2D picture (a photo taken by Curiosity’s mast camera) with someone standing in front of it, but that was not the idea here (we didn’t end up using that photo). Instead, Dawn was talking while wearing a VR headset and interacting with the 3D models she was talking about, with a secondary view of the virtual world, from the point of view of the film camera, shown on the big screen behind her. More on that later. Continue reading →

Welcome New VR Users!

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Apparently, there were good sales numbers for VR equipment prior to the holiday season, and therefore a host of new VR users are coming in just about now. This meta-post collects a bunch of stuff I’ve written (or presented) in the past that might be of interest to some of those new users. These questions/answers are not hardware-specific, meaning they apply to any current-generation VR system (Oculus Rift, HTC Vive, all the Windows Mixed Reality headsets, PlayStation VR, …), and go beyond basic tech questions such as “how do I plug this in, install drivers, …).

There is one other issue for which I do not have a full article, but it’s quite important for new users: VR sickness (aka motion sickness, simulator sickness, …). Today’s VR headsets, at least the ones doing full head tracking (that means Rift/Vive et al., and not Gear VR, Oculus Go, Google Cardboard, …) should not cause VR sickness per se. These days, it is primarily caused by artificial locomotion in games or applications, as I explain in the second presentation I linked above.

The important message is: do not attempt to fight through VR sickness! If you try to stomach it out, it will only get worse. Stop using VR the moment you feel the first symptoms, take a long break, and then try again if you want to continue with the application/game that made you sick. If you try to power through repeatedly, your body might learn to associate sickness with VR, and that might cause you to get sick even when merely thinking about VR, or smelling the headset, or similar triggers. Just don’t do it.

That’s about it; now go ahead and enjoy your shiny new VR systems!

Want to Know More?

Here are a couple of other, more hardware-specific, topics:

Set-up Instructions for Vrui with HTC Vive Head-mounted Display

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It’s been more than two years since the last time I posted set-up instructions for Vrui and HTC Vive, and a lot has changed in the meantime. While Vrui-5.0 and its major changes are still not out of the kitchen, the current release of Vrui, Vrui-4.6-005, is stable and works very well with the Vive. The recent demise of our CAVE, and our move towards VR headsets until we figure out how to fix it, have caused a lot of progress in Vrui’s set-up and user experience. The rest of this article contains detailed installation and set-up instructions, starting from where my previous step-by-step guide, “An Illustrated Guide to Connecting an HTC Vive VR Headset to Linux Mint 19 (“Tara”),” left off.

If you did not follow that guide and its prerequisite, “An Illustrated Guide to Installing Linux Mint 19 (“Tara”),” this one assumes that you already have:

  • a “gaming” or “VR ready” PC with a powerful Nvidia GeForce graphics card,
  • a full installation of a 64-bit Ubuntu-based Linux operating system, e.g., Ubuntu or Linux Mint, with the MATE desktop environment,
  • proprietary drivers for the Nvidia graphics card installed and working,
  • head-mounted display filtering disabled in the graphics card driver,
  • and a working installation of SteamVR.

If you use a Linux distribution that is not Ubuntu-based, such as my own favorite, Fedora, or another desktop environment such as Gnome Shell or Cinnamon, you will have to make some adjustments throughout the rest of this guide.

This guide also assumes that you have already set up your Vive virtual reality system, including its tracking base stations, and that your Vive headset is connected to your PC via HDMI and USB (I will publish a detailed illustrated guide on that part soon-ish). Continue reading →

How Does VR Create the Illusion of Reality?

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I’ve recently written a loose series of articles trying to explain certain technical aspects of virtual reality, such as what the lenses in VR headsets do, or why there is some blurriness, but I haven’t — or at least haven’t in a few years — tackled the big question:

How do all the technical components of VR headsets, e.g., screens, lenses, tracking, etc., actually come together to create realistic-looking virtual environments? Specifically, why do virtual environment in VR look more “real” compared to when viewed via other media, for example panoramic video?

The reason I’m bringing this up again is that the question keeps getting asked, and that it’s really kinda hard to answer. Most attempts to answer it fall back on technical aspects, such as stereoscopy, head tracking, etc., but I find that this approach somewhat misses the point by focusing on individual components, or at least gets mired in technical details that don’t make much sense to those who have to ask the question in the first place.

I prefer to approach the question from the opposite end: not through what VR hardware produces, but instead through how the viewer perceives 3D objects and/or environments, and how either the real world on the one hand, or virtual reality displays on the other, create the appropriate visual input to support that perception.

The downside with that approach is that it doesn’t lend itself to short answers. In fact, last summer, I gave a 25 minute talk about this exact topic at the 2016 VRLA Summer Expo. It may not be news, but I haven’t linked this video from here before, and it’s probably still timely:

Continue reading →

Projection and Distortion in Wide-FoV HMDs

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There is an on-going, but already highly successful, Kickstarter campaign for a new VR head-mounted display with a wide (200°) field of view (FoV): Pimax 8k. As I have not personally tried this headset — only its little brother, Pimax 4k, at the 2017 SVVR Expo — I cannot discuss and evaluate all the campaign’s promises. Instead, I want to focus on one particular issue that’s causing a bit of confusion and controversy at the moment.

Early reviewers of Pimax 8k prototypes noticed geometric distortion, such as virtual objects not appearing in the correct places and shifting under head movement, and the campaign responded by claiming that these distortions “could be fixed by improved software or algorithms” (paraphrased). The ensuing speculation about the causes of, and potential fixes for, this distortion has mostly been based on wrong assumptions and misunderstandings of how geometric projection for wide-FoV VR headsets is supposed to work. Adding fuel to the fire, the campaign released a frame showing “what is actually rendered to the screen” (see Figure 1), causing further confusion. The problem is that the frame looks obviously distorted, but that this obvious distortion is not what the reviewers were complaining about. On the contrary, this is what a frame rendered to a high-FoV VR headset should look like. At least, if one ignores lenses and lens distortion, which is what I will continue to do for now.

Figure 1: Frame as rendered to one of the Pimax 8k’s screens, according to the Kickstarter campaign. (Probably not 100% true, as this appears to be a frame submitted to SteamVR’s compositor, which subsequently applies lens distortion correction.)

Continue reading →