 The way we are developing and treating VR, it is a means to an end. We are not developing VR for its own sake, but in order to do better science. Now that you have this interface where you can work with your data in a much more natural fashion, you're not just doing your science faster, but you're doing it in a completely different way. I'm Oliver Kreilos, I'm a researcher at the University of California, Davis. I am specifically in the K-Caves project, which is an interdisciplinary research project between computer scientists like myself and earth scientists on the other side with the overarching goal to develop virtual reality as a tool to enable scientific research at a time when VR really got noticed by the mainstream for the first time in the late 80s, early 90s. Head mounted displays were the display modality of choice. The problem was that head mounted displays have two inherent issues that make them very difficult to deal with. One of them is latency that requires a very low response time between you moving and the system reacting to it. The second part is they also are very sensitive to calibration. You need to input the positions of your eyes relative to the very small screen very precisely in order to get a convincing image. And so those were both things that couldn't really be done with the technology at the time, which is one of the reasons why VR ultimately failed. People came up with the idea, well, instead of having two tiny little screens that are mounted right in front of your eyes, why not just use big screens that are far away from you and that are not attached to your face? And hence the cave was born, which is essentially a combination of three very big screens on the big floor, which are projected by big projectors. And then the user does not wear a display on their face, but they just wear stereo glasses, the same ones you would wear in a 3D movie theater. That was really the first time that a VR environment was working to the point where you could really do things in it. So the cave by design is a one person environment. Due to the way it works, it can only create a very convincing view of your virtual objects for the person who is wearing the head-track glasses. Everybody else in the cave gets a secondary, somewhat distorted view. But in practice we found that our scientists are using the cave in smaller groups. And that is when sort of the light bulb went off, when we realized that science is collaborative, not just because people work together in writing papers, but really they develop the knowledge or they extract the knowledge from the data in a collaborative fashion. Very naturally from that observation came then the question, how can we support collaborative work that is not done in the same environment, but across different environments? We are trying to replicate precisely the way how people work together when they are in the same physical space, but then we are trying to allow them to do it separately. Each one of these is a capture space, so to speak. Here in this space I am capturing the user using one, two, three first generation Kinect cameras so that we get a full body, low resolution, 3D scan of the person. And then the same thing is true for the 3D TV, only that we have only two Kinects, one to the left, one to the right, because the TV is supposed to be used sitting down in front of it like this, and so now I am captured from here and from there. Anybody who is using this environment, who is sitting here or standing here with the Rift gets transported virtually into that shared space, and the same for whoever sits in front of that. It doesn't really make a difference if this is here or in another room on campus or somewhere across town, or we have even tried it between here and Germany where latency was, let's say, the problem, but it still worked. So this is a long distance communication system. What looks like very disparate elements is, if you look at it from an underlying level and especially from a technical level, it is actually really one thing. On the one hand, we have all these different things in hardware that make VR happen. There is the Cave and the 3D TV and the Oculus Rift and the Project Morpheus and whatever you have, and then you have all these input devices from the game controller to keyboard and mouse to the kind of tracked wand that we have in the cave and stems and razor hydras and motion capture suits and all that. So these very disparate elements, those are the things that any good VR software has to unify. What I am personally working on is to write that infrastructure, that middleware that allows us to write software completely independently of any of those issues. And while that is work in progress, and I have been working on it for, I don't know, 16 years now, it works really well. What I'm trying to work towards is essentially treating VR, treating the VR environment like you would treat a normal computer, meaning that there is some VR operating system that is running on the bottom of it, but which really supports exchanging data between applications, accessing your files in some form. So in other words, some kind of 3D VR version of the kind of things that would be in a normal operating system. The main skepticism is that virtual reality or 3D doesn't really add anything to the functionality of a system. That anything we can do in VR you can also do using a normal computer, but of course at much, much, much lower cost. And that we found out is simply not true. By shifting fieldwork out of the field where you are not connected to the internet, where you don't have power, where each day in the field costs a lot of money, we can now do those things in our offices in comfort and over a much longer period of time, we can just attempt to get data that we didn't even consider doing before. For example, we can send a team of students to scan an area after an earthquake at a very, very high resolution using LiDAR and then spend months in the cave cleaning up our data to get not dozens but hundreds of measurements, which not only give us a much more detailed view of what is happening along this fault during the earthquake, but it also gives us information we simply didn't have before.
 The way we are developing and treating VR, it is a means to an end.
 We are not developing VR for its own sake, but in order to do better science.
 Now that you have this interface where you can work with your data in a much more natural
 fashion, you're not just doing your science faster, but you're doing it in a completely
 different way.
 I'm Oliver Kreilos, I'm a researcher at the University of California, Davis.
 I am specifically in the K-Caves project, which is an interdisciplinary research project
 between computer scientists like myself and earth scientists on the other side with the
 overarching goal to develop virtual reality as a tool to enable scientific research at
 a time when VR really got noticed by the mainstream for the first time in the late 80s, early
 90s.
 Head mounted displays were the display modality of choice.
 The problem was that head mounted displays have two inherent issues that make them very
 difficult to deal with.
 One of them is latency that requires a very low response time between you moving and the
 system reacting to it.
 The second part is they also are very sensitive to calibration.
 You need to input the positions of your eyes relative to the very small screen very precisely
 in order to get a convincing image.
 And so those were both things that couldn't really be done with the technology at the
 time, which is one of the reasons why VR ultimately failed.
 People came up with the idea, well, instead of having two tiny little screens that are
 mounted right in front of your eyes, why not just use big screens that are far away from
 you and that are not attached to your face?
 And hence the cave was born, which is essentially a combination of three very big screens on
 the big floor, which are projected by big projectors.
 And then the user does not wear a display on their face, but they just wear stereo glasses,
 the same ones you would wear in a 3D movie theater.
 That was really the first time that a VR environment was working to the point where you could really
 do things in it.
 So the cave by design is a one person environment.
 Due to the way it works, it can only create a very convincing view of your virtual objects
 for the person who is wearing the head-track glasses.
 Everybody else in the cave gets a secondary, somewhat distorted view.
 But in practice we found that our scientists are using the cave in smaller groups.
 And that is when sort of the light bulb went off, when we realized that science is collaborative,
 not just because people work together in writing papers, but really they develop the knowledge
 or they extract the knowledge from the data in a collaborative fashion.
 Very naturally from that observation came then the question, how can we support collaborative
 work that is not done in the same environment, but across different environments?
 We are trying to replicate precisely the way how people work together when they are in
 the same physical space, but then we are trying to allow them to do it separately.
 Each one of these is a capture space, so to speak.
 Here in this space I am capturing the user using one, two, three first generation Kinect
 cameras so that we get a full body, low resolution, 3D scan of the person.
 And then the same thing is true for the 3D TV, only that we have only two Kinects, one
 to the left, one to the right, because the TV is supposed to be used sitting down in
 front of it like this, and so now I am captured from here and from there.
 Anybody who is using this environment, who is sitting here or standing here with the
 Rift gets transported virtually into that shared space, and the same for whoever sits
 in front of that.
 It doesn't really make a difference if this is here or in another room on campus or somewhere
 across town, or we have even tried it between here and Germany where latency was, let's
 say, the problem, but it still worked.
 So this is a long distance communication system.
 What looks like very disparate elements is, if you look at it from an underlying level
 and especially from a technical level, it is actually really one thing.
 On the one hand, we have all these different things in hardware that make VR happen.
 There is the Cave and the 3D TV and the Oculus Rift and the Project Morpheus and whatever
 you have, and then you have all these input devices from the game controller to keyboard
 and mouse to the kind of tracked wand that we have in the cave and stems and razor hydras
 and motion capture suits and all that.
 So these very disparate elements, those are the things that any good VR software has to
 unify.
 What I am personally working on is to write that infrastructure, that middleware that
 allows us to write software completely independently of any of those issues.
 And while that is work in progress, and I have been working on it for, I don't know,
 16 years now, it works really well.
 What I'm trying to work towards is essentially treating VR, treating the VR environment like
 you would treat a normal computer, meaning that there is some VR operating system that
 is running on the bottom of it, but which really supports exchanging data between applications,
 accessing your files in some form.
 So in other words, some kind of 3D VR version of the kind of things that would be in a normal
 operating system.
 The main skepticism is that virtual reality or 3D doesn't really add anything to the functionality
 of a system.
 That anything we can do in VR you can also do using a normal computer, but of course
 at much, much, much lower cost.
 And that we found out is simply not true.
 By shifting fieldwork out of the field where you are not connected to the internet, where
 you don't have power, where each day in the field costs a lot of money, we can now do
 those things in our offices in comfort and over a much longer period of time, we can
 just attempt to get data that we didn't even consider doing before.
 For example, we can send a team of students to scan an area after an earthquake at a very,
 very high resolution using LiDAR and then spend months in the cave cleaning up our data
 to get not dozens but hundreds of measurements, which not only give us a much more detailed
 view of what is happening along this fault during the earthquake, but it also gives us
 information we simply didn't have before.