Making the Citadel

We just put up a video of how the Magic Citadel demo for UE4 was built:

The demo is not available yet, we are still working on the game-side of it in UE4, but the Citadel model is pretty much complete at this point. I would like to cover a couple of aspects that I find interesting from this experience.

A question I often get is why use voxels at all. I usually point at the obvious bits: If you want to do real-time constructive solid geometry (CSG) pretty much anything else is too slow. CSG is what allows to create game mechanics like harvesting, tunneling, destruction and building new things. Also, if you are doing procedural generation of anything that goes beyond heightmaps, voxels make it much easier to express and realize your procedural objects into something you can render using traditional engines like UE and Unity.

What I rarely say is that once you work with voxels, your mind changes. I let people figure this out by themselves, I do not want to be that weird guy saying you really need to try LSD. You change because you begin seeing your entire project as a single fabric of content. You feel more like you are working on a canvas. There is no difference between a tower roof versus terrain you have terraformed. It is a really distinct feel, which cannot be explained rather experienced.

If you have developed for UE4 or Unity before, think of how you would approach a project like this Citadel. While it is possible, you would be building out of a myriad of objects placed in your scene. You would have an object for the terrain, static meshes for the towers, walls, even the rocks making up your cliffs would be a bunch of instanced meshes clearly intersecting each other. Simply put, there is no canvas, instead, you have a collection of things.

If you want to have large organic shapes, like a massive spiral tower that slowly unravels over hundreds of meters, you would need to carefully plan how to deal with all this unique geometry. The image below shows an example of this from the Citadel:

It gets messy. This often leads to not having unique geometry at all, as it is too much trouble. It is unfortunate. Unique geometry can take your content to a whole new level. Once you have experienced it for a while, going back to the traditional instance-based approach is immersion breaking, at least it is for me now.

When you build out of individual small pieces, even if they have LODs of their own, their agglomeration cannot be trivially condensed into single objects that will efficiently LOD. Serious consideration needs to go into which objects you use to build the world, how large they can be, how you can reuse them and create cheap variations of them. All this planning takes a lot of work and mostly, a big deal of experience.

This is why it takes a Triple-A team to produce complex scenes and rich open worlds. Even when there is plenty of very talented artists out there, the slew of tricks you need to apply remains a veiled, mysterious art. We should not need GDC talks. The current state of the industry is as if Microsoft Word would limit the kind of novel you can write with it, and only those versed in Word's options and macros were able to create compelling fiction with it.

As I see it, it is really about the "fabric" that makes the virtual world. Once it becomes an organic canvas, you can automate tricks like LODs, culling and visibility sets in simple, robust ways. Let the computer do the hacks for you.

The other advantage of developing a virtual world as it were a canvas, is that your workflow becomes closer to what you experience working in Photoshop, versus the Maya-Blender experience. This is one of my favorite bits in the video above, it starts around the 2:54 mark. The artist first defines the basic volumes and then continues to refine them. I find this very intuitive and close to how people create in pixel-based systems like Photoshop.

Talking about artists, this Citadel project was possible thanks to Ben, who became part of the Voxel Farm team early this year. The amount of work he was able to put into this Citadel is incredible, as is the quality of his work. Ben caught everyone's attention as a player-builder in Landmark, under the Ginsan alias. Here is one voxel beauty he created back then:

Screenshot from Landmark (SOE/Daybreak)

A true Renaissance man, Ben also created the superb music for the video above. He often tweets about his progress in new Voxel Farm projects, if you are curious about what he is working on, make sure to follow him https://twitter.com/adamiseve

Is voxel data bigger than polygon data

We just got some fresh measurements that I would like to share.

Voxels and polygons are alternative forms of storing and visualizing 3D information. They are pretty much equivalent in terms you could represent the same information, the key difference is there are penalties attached to each method.

For instance, if you want to change the world in real-time, like making holes, cutting pieces or merging different shapes, voxels are likely to outperform polygons. The same applies if you want to merge layers of procedural content in real time. This is fast because voxels are a much simpler representation of the content. If you were doing this with polygons, you must use more complex and slower methods.

On the other hand, polygons can represent and reproduce some surfaces more economically. This is the reason why the graphics industry adopted polygons so early.

One aspect where we can do an apple-to-apple comparison is data size. The experiment would be this: Get a fairly large scene, store it both as voxels and polygons, and see which dataset is larger. We would be measuring the final size of the package, that is, how much data you need to download to have a complete scene.

This is what we did. We used Ben's work-in-progress scene, which features a massive citadel. The following video shows a character running around this place. You do not have to watch all this to realize it is a pretty big place:

(Please ignore the rough edges in the video, this is an un-optimized test aimed to get a feeling of the scale of the place.)

Everything you see there is voxel content. There are no props or instances. This is all unique geometry, forming a watertight mesh:

Here are the core stats about the scene:

54,080,225 triangles
2,203,456,000 voxels

This is the first takeaway. It takes 2 billion voxels to represent the same content as 54 million polygons. You need 40 times more voxels than polygons.

Is the voxel dataset 40 times the size of the polygon dataset?

That, you guessed, depends on how much smaller a voxel is than a polygon, also what is the overhead in storing them. Let's talk about that.

We store meshes as:

• a list of vertex coordinates (3 x 32bit float)
• a list of faces, where each face is three indices into the vertex list (3 x 32bit int)
• a list of UV pairs, one per each vertex in a face (2 x 32bit float)
• a list of material identifiers, one per each face (16 bit)

For the entire scene, the final compressed version of this data is 527 MB.

Voxels, on the other hand, store:

• attributes (empty, has material, has UV, etc. 8bit int)
• one 3D point (3 x 8bit float)
• up to 12 UV entries with surface properties (each 64bit)
• inner material (16bit int)

The compressed final version of the voxel data is 1,210 MB.

It seems the voxel data takes twice the space. This somehow feels right, considering everything we have heard about voxels versus polygons, it is no surprise voxels take twice the space as polygons for the same content.

But there is a little problem with this test. It is not really apples-to-apples. Here is why:

The polygon version of the content captures only the visible surfaces. That is when the solid materials meet air. These are the portions of the model you can actually see.

The voxel version of the content also captures hidden surfaces. While you cannot see these initially, they may become exposed later due to changes made by the viewer to the scene, for instance, while destroying or building things.

This image shows why these two sets of surfaces are different:

The red arrows point to surfaces that appear in the voxel set but are not included in the polygon set.

Luckily for us, we can change the contour rules and also produce these surfaces in the polygon dataset. After a collecting a new set of stats for this new configuration, the new polygon count is 122,470,300 triangles. Once this is compressed, the final storage is 1,105 MB.

Now, this has come very close to the voxel database size. Does this make any sense?

What is maybe most surprising is that we expected the sizes to be different. In both cases, we are capturing surfaces. Even if they are fully volumetric, voxels only really get "busy" around surfaces. This is not much different than polygons.

Of course, there are nuances in how the information is compressed. In each case, we could be using tailored compression schemes. But at this point, this will be producing diminishing returns, and the ratio between voxel data and polygon data is not likely to change much.

If you have questions or opinions about these measurements, I'd love to discuss them. Just post a comment below.