Ever since playing Dragon Age 2 and having finished the Mass Effect trilogy more times than I can recall, I have been plagued by one question: why does the Dragon Age series change the playable protagonist with each instalment? Post-Trespasser, this rhetorical question was followed by: I hope they don’t continue this pattern in Dragon Age 4…
This article assumes that you are at least somewhat familiar with how the Material Editor in Unreal 4 works and have a working knowledge of HLSL, in that I won’t be stopping to define a lot of concepts beforehand.
Nothing except for the math here is really that complicated though, and if you have any experience with a game engine in general, you should be fine. (and the math can be ignored and the formulae used as is)
You should understand how the custom node functions, at least somewhat if not in entirety, and more importantly, how to use it.
In case you are having trouble understanding how to implement the raymarching, this series of articles by Alan Zucconi in Unity is a great primer and is how I first got to grips with the subject.
This is what your material setup should look like in order to get the raymarching of SDFs to work (set your shading model to ‘Unlit’ when you create the material):
Code in the ‘Raymarch’ custom node is here.
The ‘SphereSDF’ node should have the HLSL version of this function, which means vec3 becomes float3.
The argument ‘p’ is the ‘WorldPosition’ argument of the raymarch node or AbsoluteWorldPosition you will be passing in from the Material graph.
There’s some stuff with local and world space to deal with that’s under ‘Coordinate spaces and conventions’.
Making material SDFs:
What I did at first was to wrap all these SDFs in custom nodes in Unreal, so that I could plug them in and out of custom nodes along with their inputs in order to pass them on.
How custom nodes function makes it necessary for the smaller SDF functions and their inputs to be plugged into the base raymarcher function, so that the HLSL translator can pick up all of them and put the function calls in the right places.
Let me be clear, this is bad and not a sustainable way to work, and not just because how the translator names these functions is entirely opaque and liable to change.
It is an awful limitation on a language that is ostensibly supposed to be a visual coding language, as it makes the act of plugging in a distance field to use as a shape (the ideal way I envisioned this working) become arduous in comparison to just typing out the code instead.
It won’t scale to more complex models as it is currently, of that I am convinced, but as a learning experiment to understand how SDFs and raymarching work its still okay.
I figured that in case you were looking forward to modelling with SDFs right out of the box using the custom nodes I’d head your expectations off at the pass, because the material editor makes achieving that type of functionality pretty hard.
I figured out a half-solution later on, it’s located after all the SDF math.
Coordinate spaces and conventions:
For converting Inigo Quilez’s SDF functions into versions usable with transforms and world space objects, keep in mind that all of his functions assume the object is centered, and where he uses length(Position), instead you would use either length(PixelWorldPosition – ActorPosition) or distance (PixelWorldPosition, ActorPosition).
The SDFs seen here use the convention of negative values being within the object and positive values failing the distance test, in other places you might see this trend reversed so its something to keep in mind.
A trick to simplify SDF for objects symmetrical about their center (like box and rounded box) is the use of abs(PixelWorldPosition) means that evaluating positions both negative and positive with relation to the center of the object can be treated the same, this simplifies quite a bit I think.
The subtraction of the box dimensions from the position being tested will determine whether the point is in the box or not, as if it is negative, then the point MUST be within the volume, as a positive result means that the point is outside the box.
It’s simple vector math that’s going on here, addition is shifting a vector along another vector, and subtraction is shifting the second vector in the opposite direction of the first vector.
The result is then fed into a max-op with a zero vector to eliminate negative values from the length check, as negative and positive values of the same vector will give the same length, but if its negative we already know its inside and hence don’t care what the actual value is.
The max is just to isolate any positive values, and then a length check is done returned to the raymarching function, compared against the minimum distance (Alan’s tutorials define this as distance-aided raymarching), and if lesser than that, the point is within the box.
Changing the swizzled operators of p.xz and p.y here to a different set of axii, would cause the torus to be aligned along a different axis.
P.xz determines which axii the torus extends along, P.y determines the axis of torus thickness.
Subtracting t.x from P.xz gives the external radial boundary, meaning t.x is the parameter that controls the outer radius of the torus. The length of p.xz and the value of p.y needs to be such that the resulting length of q is lesser than t.y (the internal radius), in order for it to be in the SDF.
The order of the elements that form q is irrelevant as we take the length of that vector.
Subtracting t.y from the final result gives the thickness of the torus.
It would seem that by combining any two axii and their vectors and taking the length of the resultant vector, we bias the SDF towards including points along those axii.
This same type of axial combination is used for cylinders too.
This formula seems to be in a bit of error as changing values of c.xy dont affect the cylinder shape, but rather cause an offset of it from the center. They can be eliminated entirely as a translation can more easily/transparently be achieved by adding an offset to the position input.
As such the only parameter that affects the cylinder shape is c.z, which changes the radius of the infinite cylinder.
Similar to how the axial combination was seen in the previous SDF, p.xz affects which axii the cylinder is oriented along.
A consistent thing you can notice is that subtracting a single float value from a distance output of a primitive causes a shape of somewhat spherical nature to emerge from the SDF.
Here the two axial combination of p.xy doesn’t determine which way the cone is pointed (as you might expect, or at least as I did), but rather which plane the base of the cone is aligned with.
Instead, p.z determines which axis is used for the tip of the cone to point to.
c.x controls the width of the base, c.y controls the narrowness of the tip.
I think the dot-product is used for component-wise multiplication here as opposed to any particular geometric purpose.
The plane formula is straightforward, it prevents values from one axis to be accepted into the SDF, and the other two axii are what the plane is aligned to.
The plane normal being (0, 0, 1) for instance will only allow values on the xy plane in the SDF (as seen in the example).
The n.w bit is for a plane offset in/opposite to the direction of the normal.
As before with the boxes, the abs(Position) is used to exploit the symmetry of this shape about its center.
h.x changes the radius of the hexagon.
h.y changes the thickness of the prism.
The q.z value is what controls the thickness axis.
The second set of values, q.x * 0.866025 + q.y * 0.5 are what control the shape of the hexagon, with the q.x * 0.866025 changing the width of the hexagon and q.y * 0.5 changing the narrowness of the hexagon.
Manipulating the q.y can yield shapes like a diamond if you increase the scalar its multiplied against.
As far as I can tell the numerical constants are magic numbers that yield the correct shape of the hexagon.
It is beyond me how anyone figured those constants out in the first place (excepting trial and error), but that’s math for you.
The q.y value controls the up vector of the hexagon. Multiplying it with a scalar < 1 decreases the height and vice versa for a scalar > 1.
Changing the axii around will change the orientation of the hexagon.
A bit later on we’ll discuss how maximum and minimum operations can be used to create intersections and unions of shapes respectively, but this is a good opportunity to see their mathematical use in an SDF.
The max here (and also in the box SDFs, but this aspect of them is more transparently visible here) is an intersection that acts as an upper bound to the values that are accepted into the SDF. Take the first max away and the hexagon becomes an infinite hexagon along the thickness axis.
Take the second max away and you’re left with an infinite diamond.
This is very similar to the hexagonal prism except that the second max operation uses the original position as opposed to the absolute value of it.
This is a strange one, requiring 4 inputs unlike most of the others which need only 2 or 3.
The input a controls where the capsule starts, and can also serve as an offset for the capsule.
The input b controls where the capsule ends and controls the direction in which the capsule extends.
Controlling the axis along which the capsule is oriented is just a matter of changing the CapsuleStart and CapsuleEnd, as opposed to any change in the axial combinations within the actual shader math.
The primary function of this SDF seems to be create a line as opposed to a capsule, and the capsule is a neat extra that you can gain by subtracting the single float value ‘CapsuleRadius’ at the very end (remember what I said about how subtracting a single float value gives you shapes of spherical nature?)
To compare this to another geometric operation, this seems similar to sweeping along a line with a certain radius, resulting in a capsule.
pa would give you a local vector with respect to the starting of the capsule, and ba would give you the non-normalized direction vector of the capsule, a line along which points would be accepted.
the calculation of h is what seems to control the actual “sweeping”, in creating a ratio between the dot products.
I’m not 100% certain why the ratios of dot products is being used here, but I’m under the impression that it constrains values that are out of the range of the capsule SDF. Any value that is beyond the SDF would result in the clamp giving the extreme values of 0 and 1.
In turn the h value is used in the next line, and if its at (or close to) the extreme values of 0 and 1, it would result in the length being a large positive value, which would mean the tested position is out of range of the SDF.
As it may be evident, math is hard, and I’m no mathemetician so I can only guess at the purpose of these operations and hope that my conclusions are accurate. I would welcome any feedback or corrections if I made a mistake, so feel free to provide them.
The clamp is what confines the SDF at the ends to taper to the capsule tips. Without it the result is an infinite cylinder.
Similar to the infinite cylinder case we start with the p.xz two-axial combination here, but then we also use the abs to exploit the symmetry of it about its origin.
Changing around the axii in p.xz and p.y changes orientation of the cylinder. P.xz is the radial axis, and p.y is the up axis.
h.x controls radius of the cylinder, h.y controls the height.
The vector d is formed from a series of straight line distance checks.
The xz plane is the plane of the radius, and the length of the vectors on it is found, and compared against the desired radius, the same happens for p.y on the up axis with h.y. If the result is <= 0, it would probably be within the SDF, but there are more ops to do still before we can know for sure.
The min & max ops don’t seem to be necessary here? Removing them didn’t affect the shape of my cylinder at all.
the max of d with 0 is to remove any negative values, as those would be within the SDF anyway but would return a large positive value when the length is taken, similar to what happened with the box SDFs. (thus invalidating a correct point which is actually within the SDF)
Capped Cone, Triangles, Quads:
I couldn’t really understand this one, and I couldn’t get it to work either. Let’s say its been left as an exercise to the reader.
Making models more complicated than the basic primitives would be very tedious considering that for every shape that you needed, you’d have to plugin a bunch of inputs to the main raymarching node in the right order which wasn’t straightforward to see and liable to change if you needed to change the order in which your shapes were input for some reason. It just wasn’t practical to do.
In this picture, each custom node has been wrapped in a Material Function, which does help in making them more reusable, as those are now accessible to any material, but you still have the issue of plugging inputs in a fragile compiler dependent order.
Doing these by code would be far faster, which defeats the purpose of using visual programming.
When I was looking for a solution for these problems I stumbled across this little gem in his blog where Ryan Brucks said that it was possible to insert HLSL functions that could be called from custom nodes.
I tossed all the SDFs (with HLSL functions wrapped around them) into ‘Common.ush’ and then was able to call these functions from the custom nodes.
This means that the material functions created earlier could serve as an in-engine documentation for the SDFs, and you can then call those SDFs directly with code in the custom nodes, removing 1 pin you need to connect for every SDF (the pin of the SDF custom node/material function) from the process.
The other issue of still having to plug in the inputs for these functions you call in code, as opposed to having all that bundled into a single input, still exists.
However this method allows for a single generic raymarch node to be used with inputs added in as needed as opposed to in the previous version where I tried to make raymarch nodes generic by how many inputs were needed by a single SDF function, which resulted in way too much spaghetti.
It also makes the process of compositing different SDFs into a single more complex shape, more feasible and scalable.
Of course the solution is now a half visual programming and half coding based approach, but there are no free lunches.
Now that the more elementary shapes are out of the way, we can start to do more cool stuff with the distance fields, like manipulate them with other operations in order to add, subtract and intersect them.
How these are supposed to be used is fairly self explanatory, the distance ops take as arguments the results from the distance fields and return the result of the respective operations they perform to the raymarcher.
The math behind them is also fairly straightforward:
The union acts as a lowerbound using the minimum, and hence biases the output towards the more negative values, meaning that, for example:
In the case of a sphere of radius 6 and a cube of side 4, both centered at the origin, the point (0, 5, 0), the result of their SDFs for this point would be -1 and 1 respectively, the union would use the minimum value and hence accept the sphere output of the SDF instead of the cube output. Hence BOTH the sphere and the cube are rendered where previously only one would be.
The intersection is the opposite of the union where the maximum is used instead and biases the output towards more positive values, so where the union would accept the volume generated by both volumes, the intersection only accepts the most conservative estimate of both volumes, i.e. the regions that are DEFINITELY within the SDFs of both volumes.
Subtraction could be said to be a special case of the intersection where by negating the values of one SDF you bias the output towards accepting the values of only one output and completely excluding the other, which gives you subtraction of the volumes.
This was an operation I REALLY wanted to learn because who doesn’t love infinitely repeating M.C. Escheresqe stuff life this?:
An issue I ran into though is that the GLSL mod and HLSL fmod aren’t completely equivalent, which is very nicely explained in this article.
I was able to perform the repetition, to a degree, but had weird artifacts like this:
To fix this, I added another function to the ‘Common.usf’ for a replacement of the GLSL mod and used that instead, which fixed the positioning errors in the repetition, but still had issues with the raymarcher for some reason:
The 9bitScience article had this warning about operations that act on the input position of the SDFs:
Which meant that by multiplying the result of the distance field with a scalar < 1, increasing the steps the raymarcher takes, and increasing the precision of the accepted distance of the raymarcher, I could finally get the results of the repetition operation correctly:
The edges of some of the boxes at the edges are still raggedy though and that stumped me for a bit until I stumbled across this video:
This video showed me that the repetition function shown on Inigo’s article might be wrong or might not work in Unreal’s setup for whatever reason as at about 18-19 mins in he shows the implementation they use in their tool which includes a ‘+ 0.5 * spacing’ as a compensation to the domain position being supplied.
This finally fixed everything for me.
Translation isn’t a big issue considering that the raymarching is already attached to an object position and hence moves with the actor anyway.
There’s two issues with implementing the rotation operation though.
One is that matrices can’t be provided as input in the material editor, though I have seen some material functions for transforming vectors that take individual basis vectors which might work if you construct the matrix in code, HLSL documentation for which you can find here.
The other issue is that unlike GLSL, HLSL doesn’t have a built in function for determining the inverse of matrices, and has a transpose method instead, which if the model matrix is orthogonal would work but that isn’t the case if the model matrix encodes a translation or scaling, as those do not preserve orthogonality.
However, I managed to hack in a limited amount of rotation functionality using some HLSL shader constants that are set per material/object before the shader is evaluated.
These are called ‘Primitive uniform shader parameters’ in Unreal and for people more familiar with GLSL (as I am), these are more simply called ‘uniforms’.
The documentation for them is decent though and lists all the ones you can use and a short comment about the purpose of the parameter.
The one you need here is ‘Primitive.LocalToWorld’, a matrix variable that contains the model transforms we need, in particular the rotation transform.
For more information on matrix transforms, this link has been my go-to reference for years now.
Keeping in mind that scaling can mess up distance fields (as its an operation that doesn’t preserve vector length), you also need to set the scale values in the model matrix back to 1 so that they don’t affect the SDFs you use them on.
After that its just a matter of multiplying it against the position input for the SDF you want to be rotated, and you have rotation of the SDF when you rotate the object!
The rotation doesn’t seem to play well with the raymarcher extreme angles (as can be seen in the gif below), it also seems to not work well with the domain repetition operation if you rotate stuff beyond a couple of degrees.
Using SDFs with non-Euclidean norms:
These can be implemented pretty easily, just make a new length function that also takes a ‘norm’ float argument in ‘Common.ush’ and you’re good to go, you can call it from other SDF functions that you add for the shapes using the new norms.
The inverse multiplication inside the primitive call confused me, but I read on a forum thread on pouet that it is to counteract the scaling of resultant distance which messes with the distance field. The reason for this being rotation and translation preserve the length of vectors, but scaling does not and Inigo mentions this in his article also.
One issue with this operator is that its hard to generalize, because it needs to be applied to both the inside and the outside of a primitive call, for each distance field operation. Thus it needs to be invoked on an individual basis for each SDF as opposed to having a function to call to do it a single time.
Displacement should be obvious, it serves to distort the primitive SDF in some manner, so I think its just a matter of trying out different functions and seeing what works for your intended look.
In the image above I’m using the displacement function Inigo mentions in his article.
The Blend operation’s purpose seems to be to eliminate the discontinuities from the union operation, but more simply it’s a function that allows for smooth interpolation between SDFs where the union would do a hard joining operation.
Twist and Bend:
The problem with these last two operators is that they aren’t giving the expected results, even with changes to the constants being used and changes to the axii to account for the different coordinate systems.
What I get are odd smeary results from the twist operation:
And results that kind of look like they’re working at some viewing angles but fall apart at others from the Bend operation.
Will keep tweaking and update this post if I get them to work right, but for now that more or less does it.
One of the games that came out recently that surprised me in terms of clever design and depth of its gameplay systems was Legend of Zelda: Breath of the Wild.
After watching the GDC 2017 talk given by the three lead developers of BotW, in particular the section given by the lead programmer:
This talk blew my mind when I first saw it.
The simplicity of the system, and the potential that it possessed, made this method seem like something every game going forward that wants to have an fully interactive world should have, in my opinion.
I started thinking about how you might implement something like this in Unreal, and moreover how you might implement it in a way that allows for ease of use and scaling as you added more materials and elements.
This also coincided with the Unreal Summer Game Jam, and I decided to take the opportunity to create a small game/proof of concept for this system:
This is what I came up with:
The rules of this system are stated quite simply and don’t leave much room for error:
1. Materials can interact with Elements
2. Elements can interact with other Elements
3. Materials cannot interact with other Materials
The system as I implemented it in Unreal has a few basic pieces:
1) Material components – Registered as a C++ base class, this is subclassed into various different Material types like WoodMaterial, MetalMaterial etc in Blueprints.
2) Element components – Registered as a C++ base class, this is subclassed into various different Element types like FireElement, WaterElement etc in Blueprints.
3) Material/Element states – Every component has a state enumeration variable, which by default is “Active” and represents that material/element after being exposed to some element, eg. “Burning”, “Wet”, “Electrocuted” etc. (these are Material state examples, I haven’t quite found a use for Element states yet beyond “Active” and “Disabled” but I’m sure they’ll come in handy at some point)
4) Material and Element types – Another enumeration variable used to identify various types of elements and materials. This variable is chosen at design time.
5) Material Class/Element Class – Another variable that is chosen at design time, this is used to know what subclass of material/element to actually use/spawn. This is also why there is a ‘CreatedMaterial’ or ‘CreatedElement’ variable, as the component in the details panel is only a base Material/Element type, and the actual component that you need is created at runtime and stored in ‘CreatedMaterial’ or ‘CreatedElement’ respectively.
I’m fairly certain there’s better ways to do this that aren’t as hacky, but it worked for me.
It’s also a bit unintuitive to have to select both a ‘Wood’ type and a ‘WoodMaterial’ material class, you’d usually expect to do one or the other, but not both, however those values are needed by the system for proper functioning, in different places.
It’s probably something you can abstract away with some boilerplate if checks, I just didn’t find it necessary to implement for a prototype.
An unexpected benefit of doing it in this somewhat unintuitive way is that you’d never need to change your Material or Element component classes when you add new types of Materials/Elements. If you were to do if-checks based on the ‘Type’ being selected, say, then you’d need to add a new if-check for every type of material/element you add, which can quickly get out of hand. The same would apply vice-versa if you were using the Class instead.
This way introduces greater chance of user error, having one of those two properties not selected will cause silent errors that are hard to find, but if that’s a tradeoff you can live with, more power to you.
6) Blueprint subclasses of Material/Element – Having the actual Material/Element behaviors be defined in BPs, allows for designers to utilize some handy flow control systems that exist in BP and allow for intuitive and scalable scripting of the interaction between different Materials and Elements.
A picture is worth a thousand words, so here’s what the BP of the wood Material component looks like:
What’s happening in the gif is that the Player is tagged as a wood Material, and walks into a volume tagged as a fire Element.
This causes them to catch on fire (as wood in fire typically does), and when that’s done it sets the player to a ‘burning/on fire’ state.
This allows for different objects to own Material or Element components, have a type (Material example would be wood, Element example would be fire), and then allow for designers to implement different types of response behavior for when an Element and Material interact, in Blueprints.
Having state values associated with both Materials and Elements, also means you can script additional or altogether different interactions based on the state of the Material/Element in question, for eg:
A wood material in its normal active state on contact with water does nothing, but a wood material in a ‘burning’ state on contact with water, has the fire removed.
It also uses the neat visual flow control of the ‘Switch-On-Enum’ nodes to keep things simple and compartmentalized for designers.
How the actual functions of the Material/Element components are triggered is done using the BeginOverlap events from colliders, which looks something like this:
Something I did for ease of use was to create a BP class which has a collider, Static/Skeletal mesh/Particle system and Material/Element component, and then designers can easily create new interactive objects by inheriting from this BP and switching around the mesh/particle system and selecting different Material/Element types.
This works okay for demo purposes but in a production environment you’d probably make those as C++ base classes too, as there’s nothing happening in the interactive item base classes that you couldn’t easily transcribe to code.
So essentially, any class that wants to use the Material/Element components, just needs to have a collider, and hook up the BeginOverlap events of that colllider to the Material/Element ‘OnStateChange’ events and provide the appropriate arguments from the object that caused the overlap.
Here’s what that looks like for a typical interactive object:
This is an Element item, which is why it checks for both Element and Material state changes from the other object. A Material item would only check for Element state changes. (remember the three rules!)
A final tidbit, though it doesn’t have anything to do with the interactive Material/Element system persay, is for how to get particles to spawn all over a skeletal mesh, which is an invaluable part of the Cascade particle system and is necessary to sell the effect of things interacting in my opinion.
The circled out Cascade emitter is where all the magic is, the details panel in the lower left is where you choose the parameter name that will point to the target actor of this particle effect.
When you want to actually create the effect, it’s just a matter of spawning the appropriate particle system, and setting that parameter using the name you assigned within the particle system earlier, to the actor that you want to be covered in fire/water/etc.
That’s it for this post, hope that this provided some insight into how to make objects feel more interactive and get more of that lovely ‘game juice’ feel into your games that Nintendo manages to do time and again.
Hope this is helpful!
I’m on Twitter and you can reach me @nightmask3 if you need any help or have a clarification.
A compilation of work I’ve done using Blender, Houdini, Adobe Creative Cloud, Quixel Suite, xNormal and Unreal 4.
What follows is a breakdown of what’s happening in each shot:
1) Interactive Electricity/Lightning effect:
After watching the Unreal Dev Days talk given by Alan Willard, the Senior Developer Relations Tech. Artist at Epic:
and his subsequent demonstration of that same effect on the UE4 livestream:
I wanted to try to replicate the effect as it depends on the interaction of all the systems of Blueprints, Materials, lights, particles and sounds in order to achieve the final effect, something I’ve never done before, and seemed like a good challenge to improve my knowledge of Unreal.
For my implementation I left out the sound but replicated everything else, as far as I can make out. I was particularly impressed by the range of options that the system provided to designers in order to tweak the effect however they want, and especially how the same asset could safely and effectively be used in multiple scenarios to achieve a variety of different visual compositions.
The system itself isn’t really that complicated once you break it down either, which is all the more impressive to my mind. It just involves raycasting in a random direction, spawning a new electric arc and particles if that cast hit something, and repeating ad nauseum.
Most of the magic really happens inside the Material, which doesn’t utilize any textures at all in order to produce the noise in the electricity, and instead uses overlapping Fast Gradient Noise at different levels of scale and tiling to produce the distortion, from the inbuilt Noise node.
The electric arc itself is a spline with a simple cylinder mesh chosen to be stretched along that spline, and the electricity Material is applied to that cylinder. This bit is accomplished using Unreal’s ‘SplineMeshComponent’ functionality.
When an arc is spawned the starting location is the origin of the spline and if the raycast hits something, the impact location is set as the end of the spline, which is then updated along with its mesh.
2) Caustics Generator:
I was working on a light study of Blade Runner 2049, of the scenes inside Wallace Corporation, a screenshot of which I’ll include:
In order to achieve a setup similar to this, I figured I’d need to learn how to generate caustics.
There’s a couple of ways to achieve this that I read of:
This method seemed more feasible and delivered higher quality, but it still didn’t meet the bar for what I wanted in this scene for two reasons:
1) It seemed like the final quality is very dependent on the resolution of the wavefront mesh, surface mesh and the grid plane you are projecting it onto, which is definitely not ideal for a realtime environment where you might want results that could even hold up in 4K and cinematics and so forth, which I think this method could not scale up to, even with GPU computation.
2) The method doesn’t seem to allow for much tweaking or changes to be achieved in the final look, limiting its potential as an actual technical art tool.
I kept searching until I stumbled across the tech demo presented by Ryan Brucks, principal technical artist at Epic, during GDC 2017, where he demonstrated a method in which he baked the results of the caustic simulation into a flipbook which could then be used at runtime with a much lower cost.
I had no idea how to achieve results like that in Unreal, but I had also seen another video where a Houdini user demonstrated something remarkably similar:
I put two and two together, and figured that I could probably generate the simulations and flipbooks in Houdini, import them into Unreal, and then play those flipbooks back in a Material and I’d have the caustics as I needed them.
I reached out to the Houdini user on a forum post and asked them about their method and they were very helpful in describing which nodes to use and what the principle behind the method was.
After a week or two of hacking away at Houdini I had what I wanted, a tool that let you generate caustics and then bake out the flipbooks.
Doing this in Houdini, has three advantages that I see:
1) Can bake out the flipbooks at any resolution, even really large ones that Unreal cannot usually support Render Targets for without causing massive slowdowns and sometimes crashes.
2) Can use different types of input noise to generate the caustics and change a bunch of parameters and options to tweak their final look before baking.
3) Method is exactly the same as the one mentioned in the Realtime caustics blogpost, but because its carried out offline, I could increase the mesh resolutions as much as I wanted until the quality met the bar I had in mind.
I also did a bit of work after this in order to make the flipbook textures tileable using information from this blogpost, also by Ryan Brucks:
This gave me tileable caustic flipbooks that could be animated within Materials using a ‘Flipbook Animation’ or ‘SubUV_Function’ node and then used as a Light Function Material or a simple Surface Material or even as a Decal Material if you wanted.
3) “The Wanderer” character model:
I’m currently working on my own game, the working title being ‘Project Gilgamesh’.
It’s a third person parkour platformer, and I wanted to take the opportunity to learn how to make a next-gen character model that utilized Unreal’s newer cloth/rigid body physics and anim dynamics features that were introduced after 4.16.
The character modelling was done in Blender, and was based in large part on these pieces of concept art for the Dr.Strange movie:
There’s also some influence from the Adeptus Mechanicus from Warhammer 40K:
UV mapping was also done in Blender.
The high poly normals were baked down in xNormal before being imported into Quixel.
Texturing was done using Quixel Suite and Photoshop CC. All the textures were worked on at 4K and then rendered down to 2K at export.
The final skeletal mesh had 4 material slots, meaning 4 draw calls for the player per frame. I might add one more for all of the emissive points on the player like the eyes, lights from the gas mask etc.
I remember reading somewhere that Unreal recommends staying within 3-5 draw calls/materials per object, though I could not find that link again for a citation so it might be hearsay, take with a grain of salt.
The character’s poly count is a little bit on the higher side, even with current gen hardware in mind, but my reasoning behind this is that I’m not going to have many (if any) other characters that will need this level of detail by far.
Most other models will either be environmental models, props and maybe a few robotic enemy types.
The base biped model was rigged in Mixamo, brought back into Blender, skinned with clothes, gas mask and belt and then imported into Unreal.
Animations that were applied to the rigged unskinned model in Mixamo could then be imported into Unreal and worked right away on the skinned version as their skeletons were the same.
Cloth was animated using Unreals new Nvcloth realtime solver and cloth toolset which allows you to paint values for the cloth simulation onto the mesh directly in the editor.
This saves a HUGE amount of time compared to the APEX cloth program that was released by Nvidia, which was also rather complicated and obscure without a lot of up-to-date documentation either.
However there are never any free lunches and there are still some drawbacks to using this cloth method, such as how more complicated cloth setups like thick cloth or multi-layered cloth setups would not be possibly with the toolset as it is currently.
Also there’s the obvious drawback of how real time cloth is never really going to look as good as cloth that is simulated offline. Not for a very long time at least.
On the whole though I think this toolset is worth learning, if you can work around the problems with it and/or they don’t matter to your use case.
The character isn’t finished yet, but its close. I want to add other things like an additional belt strap that is attached on two sides, which I’ll probably try to do with rigid bodies or anim dynamics, which allow you to drive additional bone/socket motion on top of the character’s skeletal animations.
4) Volumetric fog using custom node and HLSL:
A demonstration of a raymarched volumetric fog effect I’ve been working on for a while.
The effect raymarches forward a certain distance, samples that point in world space, uses it to generate some noise (triangle noise is what the author of the shader on ShaderToy called it), and adds a specified color to it, which is blended with the scene texture based on the scene depth, so that nearby objects are still visible/not occluded.
Does face some issues with Translucency (always troubling in a Deferred rendering setup) and can be solved by placing the post-process effect before the Translucency step in the pipeline, at the cost of a performance hit.
Uses the Custom HLSL shader node in the Materials system.
I was working on this before Epic shipped their own volumetric fog solution. You could probably achieve the same effect using volumetric particles and their global fog but I haven’t attempted to port it or experiment with that so far.
I’m always looking for new ways to add interesting visual complexity to my projects.
Personally, I have a taste for abstract and geometric art that gives off an air of mysticism and mystery, stuff like fractals, alchemical symbols, runes and glyphs are things I find very visually stimulating, and pay special attention to.
Some examples I found noteworthy are below:
Making these symbols is often going to be a process that is completely dependent on what kind of game you are working on, what kind of world it is set in, what kind of feel you aim these symbols to convey and many other factors like this.
This blog post is not intended to address the semiotics and design portion of these symbols, that is a separate topic for another day.
What it IS intended to do, is to provide the reader with some idea of how they might achieve cool looking effects like this in their own projects.
For the purpose of this post I’m going to be using Unreal Engine 4, but in practice I believe all the knowledge would be entirely applicable to Unity or Godot, maybe even your own custom engine, really any system that has a renderer with alpha transparency.
Using photography of real life symbols:
Often the best inspiration is found in the real world. The metal plates you see above are used in rituals in Hindu culture, and have a very appealing geometric aspect to them in my opinion.
Here’s what the same symbols look like in UE4:
What I did was:
To take some high-contrast photos of these plates, trying to eliminate all shadow and light information from that photo.
Open up those photos in Photoshop, and edit the pictures with the objective of converting the image into what could be thought of as a mask or heightmap (if you’re familiar with terrain generation this’ll probably be more relevant).
This is what the output should look like:
Then just import the texture into Unreal/engine of your choice and setup the Material to look something like this:
Choosing to use this as a decal or just as a normal Surface material is up to you, but I personally find decals to work great for the use case of applying these glyphs/runes to the world.
Something to take advantage of as Unreal supports decal normals, is to generate a normal map from the mask output of Photoshop/Your-editing-software-of-choice, this adds a little more lighting info. and response for the decals.
I used an online normal map generator, but I’ve since found out that solutions like this (which also includes stuff like CrazyBump) are not advisable for generating textures for production, as the tangent spaces they operate in may or may not have any correlation with Unreal’s own MikkSpaceTangent implementation, and are generally just bad anyway.
This results in textures that will produce incorrect/inaccurate lighting responses, especially in a PBR setup.
(And if you aren’t using a PBR setup while working on Unreal or Unity right now, you should really be using a PBR setup. Even stylized aesthetics still gain a lot from respecting PBR rules)
That about covers this method though.
Use WeaveSilk to generate masks:
This next bit is pretty straightforward, but is also fun to do!
There’s an online interactive art generator called ‘WeaveSilk’ that allows users to generate complicated geometric art with just a few drags and clicks of the mouse using algorithmic generation from user input.
This lets you generate some very interesting looking patterns and symbols with minimal effort and a high iteration speed.
Saving these symbols out is also just a right-click operation away.
Once obtained, you can edit it to remove the color information and convert it into a proper mask. This mask is then used in a similar way as in the above material to create results like this in-engine:
And that’s about it for this post.
I hope that by sharing some unconventional ways to generate masks, I can give other people some ideas to help them start working on their own ways to create these cool geometric symbols and patterns we all love so much.
Hope this is helpful!
I’m on Twitter and you can reach me @nightmask3 if you need any help or have a clarification.
This is part 1 of the “How Unreal Renders a Frame” series, you can access part 2 and part 3 as well.
I was looking around the Unreal source the other day and inspired by some excellent breakdowns of how popular games render a frame, I thought to try something similar with it as well, to study how it renders a frame (with the default settings/scene setup).
This is Part 1 of a series examining techniques used in game graphics and how those techniques fail to deliver a visually appealing end result. See Part… for a more thorough explanation of the idea behind it.
High dynamic range. First experienced by most consumers in late 2005, with Valve’s Half Life 2: Lost Coast demo. Largely faked at the time due to technical limitations, but it laid the groundwork for something we take for granted in nearly every blockbuster title. The contemporaneous reviews were nothing short of gushing. We’ve been busy making a complete god awful mess of it ever since.
Let’s review, very quickly. In the real world, the total contrast ratio between the brightest highlights and darkest shadows during a sunny day is on the order of 1,000,000:1. We would need 20 bits of just luminance to represent those illumination ranges, before even including color in the…
I had to make a physics engine for one of my classes at DigiPen (CS550 – Physics Simulations).
The requirements of this physics engine were:
1) Have a broadphase collision detection implementation
2) Have a method of resolving collision
3) Must use three dimensional rigid body physics
The engine uses an Entity-Component system that communicates using an Observer pattern.
A good primer on the observer pattern can be found here: http://gameprogrammingpatterns.com/observer.html
Everything in the engine that wishes to listen to events, must inherit from the interface/abstract base class Observer.
A code snippet of the Observer:Everything that wants to send events must own a Subject for that event:
Subjects can have lists of Observers who subscribe and listen for events to fire in the future, as well as send one-time “fire and forget” events to Objects as well.
This allows for event-driven communication between Observers and Objects (which most things in the engine are).
All the managers in the engine derive from Observer, allowing for them to listen to events from GameObjects, the Engine, components etc.
The component hierarchy is fairly typical:
By default, the engine uses a semi-implicit Euler integration method. RK-4 was implemented, but never required to be used. Same goes for a Verlet integrator that was also implemented.
There are some caveats to integration, such as where colliders that are marked as ‘Static’ are not integrated. This is an issue of poor component design where I require objects that don’t really need physics (namely static objects) to still own one as they contain some data that is necessary for collision detection.
An improvement to this would be to decouple the Collider and Physics components dependencies so that a Collider could function without a Physics component also belonging to the owner.
The Gilbert-Johnson-Keerthi (GJK) algorithm is used to provide a Boolean check of whether the two convex shapes that are being tested are intersecting. The strength of GJK is that it can be manipulated completely based on the type of support function (or) support map being used.
Originally, I was using the naïve method of looping through all vertices and getting the dot product of each vertex against the search direction and finding the vertex furthest along that direction. However, for a shape with the spatial symmetry about all three axes (i.e. a cube or a sphere) it is possible to use another method involving an ‘Extents’ approach, which just multiplies the sign of the search direction against the half size of the cube (or the radius of the sphere). In this engine I have only implemented cubes, so this method proved sufficient.
If/when GJK finds a simplex that encloses the origin, it passes the simplex onto EPA which attempts to locate the closest point possible to the origin in the Minkowski space, which should give the contact point, in theory.
In practice, due to the limitations of 32-bit floating point precision and math, EPA is very prone to numerical error, and as Dirk Gregorious as stated on various forums, is a method he does not personally like. I began to see why when I encountered some situations whose blame falls squarely on the imprecision of EPA and its inability to return a consistent contact point or one that can be guaranteed to be close to the center of mass.
It’s my belief that persistent manifolds in fact are a way to make up for the imprecision introduced by EPA into the resolution process, though also the issue of error in impulse solvers exacerbates this.
When EPA returns a point that is within a tolerable limit of the origin, the contact point is extrapolated using barycentric projection. There is an iteration limit of 50 to prevent the EPA from cycling infinitely.
The contact that is generated by EPA is registered using a contact/collision constraint.
This constraint is solved using a method given by Erin Catto in his paper “Iterative Dynamics using Temporal Coherence”. It involves a sequential impulse method that comes down to a linear complementarity problem that must be solved using a numerical solver of some type.
The type of solver used in the paper and here is a projected Gauss-Siedel solver, which is shown to converge faster for this use-case than the Jacobi-Hamilton solver.
The solver performs velocity correction to ensure the velocity-level constraint is satisfied and objects will no longer move into each other, and the penetration is resolved using a Baumgarte stabilization method, which massages the constraint forces to get them to do “virtual work”.
There is also a slop term that is provided on the Baumgarte stabilization to allow objects to penetrate a bit before we apply the Baumgarte term.
Lack of persistent manifolds and numerical issues with GJK and EPA mean that there are still some penetrations that can happen in some situations.
Additionally the issue of jitter can cause penetrations to happen. I plan on continuing with the implementation of this engine at least until I can obtain stable stacking, just to teach myself as well as to have that on my portfolio.
I am pretty satisfied with the final state of my engine. It’s far from perfect, but considering that last year I spent upwards of three months trying to implement OBBs using SAT and I failed utterly, the fact that I managed to implement a working engine with detection and response is honestly enough for me.
This was developed during a student project at DigiPen, the game is an exploration-adventure game, and the character is interacting with the Jellyfish in order to solve a puzzle.
I implemented everything seen in this video, including:
Scripting in Blueprints for interaction between player input and player animation state machine
Scripting for the creature response to the player and movement AI
Scripting for the blue energy jump pad
All Character/creature/environment art, VFX, animations seen in the video
Part of the same project as the previous video, here the player completes a quest for an NPC by filling a pot with some water, and completes a puzzle by bringing a keystone to the lock-pedestal.
I implemented everything seen in the video including:
Scripting for interaction with the chest and objects the player can pick up (pot and the keystone)
All items that can be carried inherit from a Parent Blueprint with all the behavior to detect whether or not the player has attempted to pick it up, a Child Blueprint can then define what the object actually does when the player picks it up as well as the static mesh/collider etc.
Scripting, animations and animation state machine handling for the pickup and throwing actions
Scripting for interaction with NPC and the quest
Scripting for the puzzle
All art, VFX in the video except for the trail particles the player leaves behind.
An early prototype I made for a character movement ability. The player is creating this ice/crystal path in front of them using ‘mana’ as a resource to build it. The initial idea revolved around this as the short-term gameplay loop.
Implemented the scripting for the path creation on player input, it was built for a controller primarily and involved using the analog sticks to direct the path while holding down a button to create it.
Used the SplineMeshComponent provided in Unreal to define a spline that is updated dynamically in-game as the player extends the path. The component takes the spline and deforms a mesh along it, which gives the path its smooth and sinuous appearance.
The player could fly whenever they were above this path, allowing them to use it like an actual path/shortcut through the world.
Also implemented the survival gameplay seen in the HUD bars, which involve an Exposure stat that increased whenever the player was directly exposed to the sun, a Hydration stat that depleted over time and required the player to drink water or otherwise sustain damage to Health.
All art and VFX seen are created by me.
Did NOT implement the character model or animations though, those are provided by Unreal in the Third Person Template.