I recently saw something that set me wondering how to create a realistic-looking (2D) lava lamp-like animation, for a screen-saver or game.
It would of course be possible to model the lava lamp's physics using partial differential equations, and to translate that into code. However, this is likely to be both quite difficult (because of several factors, not least of which is the inherent irregularity of the geometry of the "blobs" of wax and the high number of variables) and probably computationally far too expensive to calculate in real time.
Analytical solutions, if any could be found, would be similarly useless because you would want to have some degree of randomness (or stochasticity) in the animation.
So, the question is, can anyone think of an approach that would allow you to animate a realistic looking lava lamp, in real time (at say 10-30 FPS), on a typical desktop/laptop computer, without modelling the physics in any great detail? In other words, is there a way to "cheat"?
One way to cheat might be to use a probabilistic cellular automaton with a well-chosen transition table to simulate the motion of the blobs. Some popular screensavers (in particular ParticleFire) use this approach to elegantly simulate complex motions in 2D space by breaking the objects down to individual pixels and then defining the ways in which individual pixels transition by looking at the states of their neighbors. You can get some pretty emergent behavior with simple cellular automata - look at Conway's game of life, for example, or this simulation of a forest fire.
LavaLite is open source. You can get code with the xscreensaver-gl package in most Linux distros. It uses metaballs.
Related
As I understand it, ray tracing as used in computer graphics is "geometrical optics" and no wave phenomena are taken into account.
Is there a way to include it anyway in an efficient way, or are there known tricks to fake these concepts into a ray tracing algorithm? My intuitive answer would be no; wave optical simulations are not fast enough for computer gaphics purposes.
tiny update: Are there computer graphics ray tracing algorithms/implementations that can simulate white light dispersing on/through a prism?
I've never seen a graphics rendering software package that used anything other than Geometrical Optics for scene illumination, and I guess it's mainly because you don't visually witness many of the wave effects most of the time so GO is good enough.
Some renderers use at least Physical Optics at the gathering step (when computing light returning to an observer) to account for certain phenomena but no creeping wave effects or interference there.
However there certainly are lots of computational electromagnetics software packages out there that use other models accounting for such effects, and specialized software for photonics where wave effects are really important.
Some of those software use algorithms based on Geometrical Optics that are not too far from the classical raytracing approach (adaptative beam tracing with beam subdivision based on scene geometry, shooting and bouncing rays, ...).
Some software even take advantage of the parallel processing power of GPUs.
However such algorithms are generally really specialized for one kind of problem and don't scale well for whatever wave lengths or scene sizes because they have to take the boldest simplification hypotheses possible for a given class of problems to make computations fast.
I worked on one algorithm that used raytracing and took interferences into account (among other things) to simulate RADARs used in automotive applications at interactive-ish speeds, but it could not be used for simulating anything else. There are also some proposal for taking diffraction and creeping wave effects into account with raytracing.
It's really a matter of knowing what you want to simulate and what are the features of the output you are interested in, then trade of performance and realism. The only realtime electromagnetics simulator that can take all wave effects into account at every wave length for all scene sizes that I can think of is the real world. ;-)
Also don't forget that a lot of computer graphics techniques come from computational electromagnetics. There are lots of academic resources in this field regarding wave effects that are generally overlooked in CG, along with technical solutions to take those effects into account.
After a while of 3d modelling and enjoying ZBrush's impeccable performance and numerous features I thought it would be great OpenGL practice for me to create something similar, just a small sculpting tool. Sure enough I got it done, I couldn't match ZBrush's performance of course seeing as how a brigade of well payed professionals outmatch a hobbyist. For the moment I just assumed ZBrush was heavily hardware accelerated, imagine my surprise when I found out it's not and furthermore it uses neither opengl or direct3d.
This made me want to learn graphics on a lower level but I have no clue where to start. How are graphics libraries made and how does one access the framebuffer without the use of opengl. How much of a hassle would it be to display just a single pixel without any preexisting tools and what magic gives ZBrush such performance.
I'd appreciate any info on any question and a recommendation for a book that covers any of these topics. I'm already reading Michael Abrash's Graphics Programming Black Book but it's not really addressing these matters or I just haven't reached that point yet.
Thank you in advance.
(Please don't post answers like "just use opengl" or "learn math", this seems to be the reaction everywhere I post this question but these replies are off topic)
ZBrush is godly in terms of performance but I think it's because it was made by image processing experts with assembly expertise (it's also likely due to the sheer amount of assembly code that they've been almost 20 years late in porting to 64-bit). It actually started out without any kind of 3D sculpting and was just a 2.5D "pixol" painter where you could spray pixels around on a canvas with some depth and lighting to the "pixols". It didn't get sculpting until around ZB 1.5 or so. Even then it impressed people with how fast you could spray these 2.5D "pixols" around on the canvas back when a similarly-sized brush just painting flat pixels with Photoshop or Corel Painter would have brought framerates to a stutter. So they were cutting-edge in performance even before they tackled anything 3D and were doing nothing more than spraying pixels on a canvas; that tends to require some elite micro-optimization wizardry.
One of the things to note about ZB when you're sculpting 20 million polygon models with it is that it doesn't even use GPU rasterization. All the rasterization is done in CPU. As a result it doesn't benefit from a beefy video card with lots of VRAM supporting the latest GLSL/HLSL versions; all it needs is something that can plot colored pixels to a screen. This is probably one of the reasons it uses so little memory compared to, say, MudBox, since it doesn't have to triple the memory usage with, say, VBOs (which tend to double system memory usage while also requiring the data to be stored on the GPU).
As for how you get started with this stuff, IMO a good way to get your feet wet is to write your own raytracer. I don't think ZBrush uses, say, scanline rasterization which tends to rise very proportionally in cost the more polygons you have, since they reduce the number of pixels being rendered at times like when you rotate the model. That suggests that whatever technique they're using for rasterization is more dependent in terms of performance by the number of pixels being rendered rather than the number of primitives (vertices/triangles/lines/voxels) being rendered. Raytracing fits those characteristics. Also IMHO a raytracer is actually easier to write than a scanline rasterizer since you don't have to bother with tricky cases so much and elimination of overdrawing comes free of charge.
Once you got a software where the cost of an operation is more in proportion to the number of pixels being rendered than the amount of geometry, then you can throw a boatload of polygons at it as they did all the way back when they demonstrated 20 million polygon sculpting at Siggraph with silky frame rates almost 17 years ago.
However, it's very difficult to get a raytracer to update interactively in response to mesh data that is being not only sculpted interactively, but sometimes having its topology being changed interactively. So chances are that they are using some data structure other than your standard BVH or KD-Tree as popular in raytracing, and instead a data structure which is well-suited for dynamic meshes that are not only deforming but also having their topology being changed. Maybe they can voxelize and revoxelize (or "pixolize" and "repixolize") meshes on the fly really quickly and cast rays directly into the voxelized representation. That would start to make sense given how their technology originally revolved around these 2.5D "pixels" with depth.
Anyway, I'd suggest raytracing for a start even if it's only just getting your feet wet and getting you nowhere close to ZB's performance just yet (it's still a very good start on how to translate 3D geometry and lighting into an attractive 2D image). You can find minimal examples of raytracers on the web written with just a hundred lines of code. Most of the work typically in building a raytracer is performance and also handling a rich diversity of shaders/materials. You don't necessarily need to bother with the latter and ZBrush doesn't so much either (they use these dirt cheap matcaps for modeling). Then you'll likely have to innovate some kind of data structure that's well-suited for mesh changes to start getting on par with ZB and micro-tune the hell out of it. That software is really on a whole different playing field.
I have likewise been so inspired by ZB but haven't followed in their footsteps directly, instead using the GPU rasterizer and OpenGL. One of the reasons I find it difficult to explore doing all this stuff on the CPU as ZB has is because you lose the benefits of so much industrial research and revolutionary techniques that game engines and NVidia and AMD have come up with into lighting models in realtime and so forth that all benefit from GPU-side processing. There's 99% of the 3D industry and then there's ZBrush in its own little corner doing things that no one else is doing and you need a lot of spare time and maybe a lot of balls to abandon the rest of the industry and try to follow in ZB's footsteps. Still I always wish I could find some spare time to explore a pure CPU rasterizing engine like ZB since they still remain unmatched when your goal is to directly interact with ridiculously high-resolution meshes.
The closest I've gotten to ZB performance was sculpting 2 million polygon meshes at over 30 FPS back in the late 90s on an Athlon T-Bird 1.2ghz with 256MB of RAM, and that was after 6 weeks of intense programming and revisiting the drawing board over and over in a very simplistic demo, and that was a very rare time where my company gave me so much R&D time to explore what ZB was doing. Still, ZB was handling 5 times that geometry at the same frame rates even at that time and on the same hardware and using half the memory. I couldn't even get close, though I did end up with a newfound respect and admiration for the programmers at Pixologic. I also had to insist to my company to do the research. Some of the people there thought ZBrush would never become anything noteworthy and would just remain a cutesy artistic application. I thought the opposite since I saw something revolutionary long before it acquired such an epic following.
A lot of people at the time thought ZB's ability to handle so many polygons was impractical and that you could just paint bump/normal/displacement maps and add whatever details you needed into textures. But that's ignoring the workflow side of things. When you can just work straight with epic amounts of geometry, you get to uniformly apply the same tools and workflow to select vertices, polygons, edges, brush over things, etc. It becomes the most straightforward way to create such a detailed and complex model, after which you can bake out the details into bump/normal/displacement maps for use in other engines that would vomit on 20 million polygons. Nowadays I don't think anyone still questions the practicality of ZB.
[...] but it's not really addressing these matters or I just haven't
reached that point yet.
As a caveat, no one has published anything on how to achieve performance rivaling ZB. Otherwise there would be a number of applications rivaling its performance and features when it comes to sculpting, dynamesh, zspheres, etc and it wouldn't be so amazingly special. You definitely need your share of R&D to come up with anything close to it, but I think raytracing is a good start. After that you'll likely need to come up with some really interesting ideas for algorithms and data structures in addition to a lot of micro-tuning.
What I can say with a fair degree of confidence is that:
They have some central data structure to accelerate rasterization that can update extremely quickly in response to changes the user makes to a mesh (including topological ones).
The cost of rasterization is more in proportion to the number of pixels rendered rather than the size of the 3D input.
There's some micro-optimization wizardry in there, including straight up assembly coding (I'm quite certain ZB uses assembly coding since they were originally requiring programmers to have both assembly and C++ knowledge back when they were hiring in the 2000s; I really wanted to work at Pixologic but lacked the prerequisite assembly skills).
Whatever they use is pretty light on memory requirements given that the models are so dynamic. Last time I checked, they use less than 100MB per million polygons even when loading in production models with texture maps. Competing 3D software with the exception of XSI can take over a gigabyte for the same data. XSI uses even less memory than ZB with its gigapoly core but is ill-suited to manipulating such data, slowing down to a crawl (they probably optimized it in a way that's only well-suited for static data like offloading data to disk or even using some expensive forms of compression).
If you're really interested in exploring this, I'd be interested to see what you can come up with. Maybe we can exchange notes. I've devoted much of my career just being interested in figuring out what ZB is doing, or at least coming up with something of my own that can rival what it's doing. For just about everything else I've tackled over the years from raytracing to particle simulations to fluid dynamics and video processing and so forth, I've been able to at least come up with demos that rival or surpass the performance of the competition, but not ZBrush. ZBrush remains that elusive thorn in my side where I just can't figure out how they manage to be so damned efficient at what they do.
If you really want to crawl before you even begin to walk (I think raytracing is a decent enough start, but if you want to start out even more fundamental) then maybe a natural evolution is to first just focus on image processing: filtering images, painting them with brushes, etc, along with some support for basic vector graphics like a miniature Photoshop/Illustrator. Then work your way up to rasterizing some basic 3D primitives, like maybe just a wireframe of a model being rendered using Wu line rasterization and some basic projection functions. Then work your way towards rasterizing filled triangles without any lighting or texturing, at which point I think you'll get closer to ZBrush focusing on raytracing rather than scanline with a depth buffer. However, doing a little bit of the latter might be a useful exercise anyway. Then work on rendering lit triangles, maybe starting with direct lighting and just a single light source, just computing a luminance based on the angle of the normal relative to the light source. Then work towards textured triangles using baycentric coordinates to figure out what texels to render. Then work towards indirect lighting and multiple light sources. That should be plenty of homework for you to develop a fairly comprehensive idea of the fundamentals of rasterization.
Now once you get to raytracing, I'm actually going to recommend one of the least efficient data structures for the job typically: octrees, not BVH or KD-Tree, mainly because I believe octrees are probably closer to allowing what ZB allows. Your bottlenecks in this context don't have to do with rendering the most beautiful images with complex diffuse materials and indirect lighting and subpixel samples for antialiasing. It has to do with handling a boatload of geometry with simple lighting and simple shaders and one sample per pixel which is changing on the fly, including topologically. Octrees seem a little better suited in that case than KD-tree or BVHs as a starting point.
One of the problems with ignoring the fundamentals these days is that a lot of young developers have lost that connection from, say, triangle to pixel on the screen. So if you don't want to take such rasterization and projection for granted, then your initial goal is to project 3D data into a 2D coordinate space and rasterize it.
If you want a book that starts at a low level, with framebuffers and such, try Computer Graphics: Principles and Practice, by Foley, van Dam, et al. It is an older, traditional text, but newer books tend to have a higher-level view. For a more modern text, I can also recommend 3D Computer Graphics by Alan Watt. There are plenty of other good introductory texts available -- these are just two that I am personally familiar with.
Neither of the above books are tied to OpenGL -- if I recall correctly, they include the specific math and algorithms necessary to understand and implement 3D graphics from the bottom up.
In a game such as Warcraft 3 or Age of Empires, the ways that an AI opponent can move about the map seem almost limitless. The maps are huge and the position of other players is constantly changing.
How does the AI path-finding in games like these work? Standard graph-search methods (such as DFS, BFS or A*) seem impossible in such a setup.
Take the following with a grain of salt, since I don't have first-person experience with pathfinding.
That being said, there are likely to be different approaches, but I think standard graph-search methods, notably (variants of) A* are perfectly reasonable for strategy games. Most strategy games I know seem to be based on a tile system, where the map is comprised of little squares, which are easily mapped to a graph. One example would be StarCraft II (Screenshot), which I'll keep using as an example in the remainder of this answer, because I'm most familiar with it.
While A* can be used for real-time strategy games, there are a few drawbacks that have to be overcome by tweaks to the core algorithm:
A* is too slow
Since an RTS is by definion "real time", waiting for the computation to finish will frustrate the player, because the units will lag. This can be remedied in several ways. One is to use Multi-tiered A*, which computes a rough course before taking smaller obstacles into account. Another obvious optimization is to group units heading to the same destination into a platoon and only calculate one path for all of them.
Instead of the naive approach of making every single tile a node in the graph, one could also build a navigation mesh, which has fewer nodes and could be searched faster – this requires tweaking the search algorithm a little, but it would still be A* at the core.
A* is static
A* works on a static graph, so what to do when the landscape changes? I don't know how this is done in actual games, but I imagine the pathing is done repeatedly to cope with new obstacles or removed obstacles. Maybe they are using an incremental version of A* (PDF).
To see a demonstration of StarCraft II coping with this, go to 7:50 in this video.
A* has perfect information
A part of many RTS games is unexplored terrain. Since you can't see the terrain, your units shouldn't know where to walk either, but often they do anyway. One approach is to penalize walking through unexplored terrain, so units are more reluctant to take advantage of their omniscience, another is to take the omniscience away and just assume unexplored terrain is walkable. This can result in the units stumbling into dead ends, sometimes ones that are obvious to the player, until they finally explore a path to the target.
Fog of War is another aspect of this. For example, in StarCraft 2 there are destructible obstacles on the map. It has been shown that you can order a unit to move to the enemy base, and it will start down a different path if the obstacle has already been destroyed by your opponent, thus giving you information you should not actually have.
To summarize: You can use standard algorithms, but you may have to use them cleverly. And as a last bonus: I have found Amit’s Game Programming Information interesting with regard to pathing. It also has links to further discussion of the problem.
This is a bit of a simple example, but it shows that you can make the illusion of AI / Indepth Pathfinding from a non-complex set of rules: Pac-Man Pathfinding
Essentially, it is possible for the AI to know local (near by) information and make decisions based on that knowledge.
A* is a common pathfinding algorithm. This is a popular game development topic - you should be able to find numerous books and websites that contain information.
Check out visibility graphs. I believe that is what they use for path finding.
So I stumbled upon this "new" graphics engine/technology called Unlimited Detail.
This seems to be pretty interesting granted it's real and not a fake.
They have some videos explaining the technology but they only scratch the surface.
What do you think about it? Is it programmatically possible?
Or is it just a scam for investors?
Update:
Since the only answer was based on voxels I have to copy this from their site:
Unlimited Details method is very different to any 3D method that has been invented so far. The three current systems used in 3D graphics are Ray tracing polygons and point cloud/voxels, they all have strengths and weaknesses. Polygons runs fast but has poor geometry, Ray-trace and voxels have perfect geometry but run very slowly.
Unlimited Detail is a fourth system, which is more like a search algorithm than a 3D engine
The underlying technology is related to something called sparse voxel octrees (see, e.g., this paper), which aren't anything incredibly amazing. What the video doesn't tell you is that these are not at all suited for things that need to be animated, so they're of limited use for anything that uses procedural animation (e.g., all ragdoll physics, etc.). So they're very inflexible. You can get great detail, but you get it in a completely static world.
A rough summary of where things stand with this technology in mainstream games is here. You will also want to check out Samuli Laine's work; he's a Finnish researcher who is focusing a great deal of his attention on this subject and is unlocking some of the secrets to implementing it well.
Update: Yes, the website says it's not "voxel-based". I suspect this is merely an issue of semantics, however, in that what they're using are essentially voxels, but because it's not exactly a voxel they feel safe in being able to claim that it's not voxel-based. In any case, the magic isn't in how similar to a voxel it is -- it's how they select which voxels to actually show. This is the primary determinant of speed.
Right now, there is no incredibly fast way to show voxels (or something approximating a voxel). So either they have developed a completely new, non-peer-reviewed method for filtering voxels (or something like them), or they're lying.
You might find more detail in the following patents:
"A Computer Graphics Method For Rendering Three Dimensional Scenes"
"A Method For Efficent Streaming Of Octree Data For Access"
- Each voxel (they call it a "node") is represented as a single bit, along with information voxels at a finer level of detail.
The full-text can be viewed online here:
https://www.lens.org/lens/search?q=Euclideon+Pty+Ltd&l=en
or
http://worldwide.espacenet.com/searchResults?submitted=true&query=EUCLIDEON
There's a lot of literature on collision detection, and I've read at least a big enough portion of it to be fairly familiar with most techniques. However, there's something that has eluded me for a while, and I figured, since StackOverflow provides access to a large group of brilliant minds at once, I'd ask here first before digging around in the bookshelf.
In this day and age, more and more work is being delegated to GPU rather than CPU, and in a lot of cases this is a good thing. For example, there are geometry shaders to create new geometry, or (slightly less new, but still quite fascinating) vertex shaders to which you can through a bunch of vertexes at, and something elegant will come out of it. What I was considering though, as these primitives exists only on the graphics hardware, how would you perform reliable collision detection with these primitives? Let's assume I have some kind of extremely simplified mesh which is displaced in a vertex shader (I don't have a concrete problem, I'm more playing with the idea, and I haven't gotten very deep into geometry shaders yet).
What I've considered so far is separate 'rendering' passes from suitable angles with shading more or less turned off, and perhaps lower resolution mesh, rendering the inside (with faces flipped inward) of my second primitive along with the mesh I want to test against, and executing an occlusion query for the mesh. If the mesh is completely occluded there'd be no intersection. This would of course require that my second primitive is convex.
Somehow I get the feeling that this kind of test will be extremely expensive as the number of primitives increase (even if a large portion can be culled directly). Does anyone else have another idea or technique? I'm more familiar with opengl and cg than directx, but if you have some examples or so in directx, I guess I'll be able to figure out the opengl counterparts.
All ideas are appreciated, so please brainstorm. :)
It sounds like Dan Horn's article “Stream Reduction Operations for GPGPU Applications” in GPU Gems 2 is exactly what you want. Like all chapters, it's freely available online.