The following video shows a result of my last year study on fractal surfaces:
It is based on surface modeling ideas that I already developed 5 years ago - as you can see in the very short video in the previous post. However, this time I have pushed the algorithm to its limits and optimized for deeper zoom levels and scaling factors. And yeah, video is longer too!
On a side note, as you can judge by the frequency of my posts here, I don't have much time lately for my spare time projects, but hey, I'm still doing "something".
Showing posts with label computer graphics. Show all posts
Showing posts with label computer graphics. Show all posts
Saturday, 14 March 2015
Thursday, 28 October 2010
Fractal surfaces
I was working hard recently on a new fractal surface generator and renderer. It is based on my theoretical research in generating fractal surfaces. Here is a very short movie, the first test:
It is rendered in 3D (stereoscopy). Unfortunately YouTube doesn't support NVidia 3D Vision glasses. Anaglyphic looks ok though.
It is rendered in 3D (stereoscopy). Unfortunately YouTube doesn't support NVidia 3D Vision glasses. Anaglyphic looks ok though.
Thursday, 7 January 2010
2D is a special effect, 3D is not
Many people are talking about stereoscopic 3D technology now, thanks to Avatar The Movie, created by a bunch of professional CG artists, hardware and software developers. I want to add my 3 cents into it.
As a little kid I loved making 3D shapes (vehicles, cones, spheres, etc..) from cardboard. Imitating the real thing you may say. Recently, I had finally a chance to experience CAVE environment, it was quite new experience, even that I was already using stereoscopic setup for many years, after that, suddenly, the childish dreams returned!
I imagined myself holding my cardboard 3D car again, but in a more flexible environment. Virtual or not, it was real!
Some people would probably like to draw a car on a paper instead of making inacurate reality imitation. They usually have a very good talent to catch the very essence of reality and show it in a different form using their own stylization and augmentation, i.e. by leaving uninteresting details behind, enchancing key features, suggesting new, interesting point of view that we didn't think of. This techniques I consider as a stylization effect. You may increase contrast of your photo to make it more dramatic. Finally, you may use greyscale or even black and white stylization and concentrate on a message. Yes, it's a fact, greyscale/b&w movies are still in production. But nowadays it is not a consequence of immature technology, it is a special effect, a feature!
The very same analogy applies to 3D movies. As our parents were used to watch movies in greyscale (or some pathetic color hacks), we are used to watch movies in full-color, but still enjoy artistic sepia or b&w in some cases. You may not realize it now, but 2D is just a stylization as well. Do you know "pin hole" camera? It allows to overcome natural depth of field problems, sometimes photo makers are using something completely opposite - they try to maximize depth of field effect (making uninteresting things completely blurred). Our eyes suffer for similar problem - we cannot see sharp picture on every distance all at once. What is worse, the eye convergence doesn't help much here either, basically we see in a good quality only the object in focus. So 2D can be a reality augmentation effect - we can "cast" objects at various distances onto one plane and "see more at once". It is not exactly "more", because we are losing depth information, but it is a different point of view, just a stylization effect, one of many! (and the palette of such effects in 3D will even increase)
As a conclusion my prediction about 3D is like this: sooner or later (after technology will be more mature, no glasses, no headaches, etc..), most TV sets will be 3D, but some people will watch 2D movies still on them - as an underground/cool artistic stylization.
As a little kid I loved making 3D shapes (vehicles, cones, spheres, etc..) from cardboard. Imitating the real thing you may say. Recently, I had finally a chance to experience CAVE environment, it was quite new experience, even that I was already using stereoscopic setup for many years, after that, suddenly, the childish dreams returned!
I imagined myself holding my cardboard 3D car again, but in a more flexible environment. Virtual or not, it was real!
Some people would probably like to draw a car on a paper instead of making inacurate reality imitation. They usually have a very good talent to catch the very essence of reality and show it in a different form using their own stylization and augmentation, i.e. by leaving uninteresting details behind, enchancing key features, suggesting new, interesting point of view that we didn't think of. This techniques I consider as a stylization effect. You may increase contrast of your photo to make it more dramatic. Finally, you may use greyscale or even black and white stylization and concentrate on a message. Yes, it's a fact, greyscale/b&w movies are still in production. But nowadays it is not a consequence of immature technology, it is a special effect, a feature!
The very same analogy applies to 3D movies. As our parents were used to watch movies in greyscale (or some pathetic color hacks), we are used to watch movies in full-color, but still enjoy artistic sepia or b&w in some cases. You may not realize it now, but 2D is just a stylization as well. Do you know "pin hole" camera? It allows to overcome natural depth of field problems, sometimes photo makers are using something completely opposite - they try to maximize depth of field effect (making uninteresting things completely blurred). Our eyes suffer for similar problem - we cannot see sharp picture on every distance all at once. What is worse, the eye convergence doesn't help much here either, basically we see in a good quality only the object in focus. So 2D can be a reality augmentation effect - we can "cast" objects at various distances onto one plane and "see more at once". It is not exactly "more", because we are losing depth information, but it is a different point of view, just a stylization effect, one of many! (and the palette of such effects in 3D will even increase)
As a conclusion my prediction about 3D is like this: sooner or later (after technology will be more mature, no glasses, no headaches, etc..), most TV sets will be 3D, but some people will watch 2D movies still on them - as an underground/cool artistic stylization.
Tuesday, 1 September 2009
New York, New York...
This summer, I work with my friend Ken at Brown University. I'm in his home country first time, so we decided to visit as Frank Sinatra sings "New York, New York...", the so called Big Apple, and it was even close enough to get there (2-3 hours by train). And what do you think was the most exciting part for us in such anomalously big city ?
Geometry, of course!
We decided to go to Empire State Building observatory during the night, and it was the right thing to do, the city lights are just breath-taking! You can enjoy the full power of human civilisation in just one spot!
Now, I consider sunset to be even more exciting time to go, especially if you wait after it will get completely dark and lights start to appear slowly - as far as my imagination is right about it (just be prepared for a very long waiting line or simply pay extra fee for VIP pass through).
After listening to interesting audio tour with a lot of nice, but sometimes a bit fake/artificial impressions, like "I just looove this city, as a young boy I loooved to walk on Brooklyn Bridge, etc..." (similar style of making audio tour you can experience at Boston's Prudential Tower aka Skywalk Observatory), I noticed that, there are two interesting aspects you should take into account when developing... NY-like city generation algorithm.
Can you spot so called Flatiron Building on the photo ? This was the most inspiring example to me. Generally, I divided buildings into two categories: first contains bulidngs that shape fits into street design, the second category contains the rest (buildings that for some reasons, use inefficient amount of space - as Ken noticed). And what is apparent in New York, there are many buildings that efficiently and as many that are inefficiently occuping space between streets (and in general, there are too many of them ;)). Flatiron has sharp angle and is efficient, while there are some with angle more than 90 deg. (where Broadway cross Avenues at more than 90 deg. angle, just note the small building on the bottom-right), some are just square-shaped even if there is so much room around them. I was so excited about this discovery that I almost forgot to enjoy the view in ehm.. humanistic kind of way :)
Geometry, of course!
We decided to go to Empire State Building observatory during the night, and it was the right thing to do, the city lights are just breath-taking! You can enjoy the full power of human civilisation in just one spot!
Now, I consider sunset to be even more exciting time to go, especially if you wait after it will get completely dark and lights start to appear slowly - as far as my imagination is right about it (just be prepared for a very long waiting line or simply pay extra fee for VIP pass through).
After listening to interesting audio tour with a lot of nice, but sometimes a bit fake/artificial impressions, like "I just looove this city, as a young boy I loooved to walk on Brooklyn Bridge, etc..." (similar style of making audio tour you can experience at Boston's Prudential Tower aka Skywalk Observatory), I noticed that, there are two interesting aspects you should take into account when developing... NY-like city generation algorithm.
Can you spot so called Flatiron Building on the photo ? This was the most inspiring example to me. Generally, I divided buildings into two categories: first contains bulidngs that shape fits into street design, the second category contains the rest (buildings that for some reasons, use inefficient amount of space - as Ken noticed). And what is apparent in New York, there are many buildings that efficiently and as many that are inefficiently occuping space between streets (and in general, there are too many of them ;)). Flatiron has sharp angle and is efficient, while there are some with angle more than 90 deg. (where Broadway cross Avenues at more than 90 deg. angle, just note the small building on the bottom-right), some are just square-shaped even if there is so much room around them. I was so excited about this discovery that I almost forgot to enjoy the view in ehm.. humanistic kind of way :)
Wednesday, 30 July 2008
Procedural graphics: science or art ?
Scientists credo seems to be: all hypotheses must be supported by the data. It's resonable. Typical scientific discovery recipe: gather a lot of data, use statistics, formulate "rules", falsify.
Statistics is math. Linear regression is a kind of curve fitting is a kind of approximation technique. Regularities (low-order curves) are common: planet bodies, planet orbits or pendulum oscillation. But so are irregularities: rocks, coastlines, clouds, fixational eye movement.
And here is the discovery that influenced my interests and research topic a lot: fractal geometry. Fractals provide sort of evidence that irregular "things" can be described as simply as regular. But there is a small twist here!
For example take some long sequence of random (white noise) data. How to approximate those date ? Is there any simple recursive or any other equation that can describe this sequence or at least fit to it with a small error ?
Unfortunately, in general, it's almost impossible to find a short one. To give you more clue - white noise doesn't compress easily (just try JPG or ZIP on it).
But we can do something else with it. We change the way we think about approximation! Instead of trying to fit all the data, we can just try to reproduce their "general characteristics". Why not "approximate" white noise just by any other white noise, i.e. generated using simple LCG? If our application is audio-visual, we will not see much difference. This kind of reasoning was succesfully used in speech synthesisers or synthetic terrain/rocks generators. And taken to the extreme (applied to vast variety of signals) define what is called: procedural art.
A procedural technique researcher is trying to find methods (a set of rules, algorithms or equations) that can be used to generate very complicated signals that has the same "general characteristic" as modeled signals, while procedural artist is trying to "paint" with those methods.
I did several procedural works in my life, i.e. a movie inside weird caves and 64k intro, introducing my own procedural techniques.
More works like this can be found in so called demoscene archives, most recommended are some Inigo Quilez works. Another prominient researcher (not related to demoscene) is Dmytry Lavrov.
With a demoscene you have to be careful though: not all those little creations are fitting my procedural art definition. Some of them just use standard approximation techniques to describe regular "things" using subdivision surfaces, quantization, wavelet compression, etc... To put it straight, this creations have lower artistic value for me (but I'm not claiming they have no value at all).
Statistics is math. Linear regression is a kind of curve fitting is a kind of approximation technique. Regularities (low-order curves) are common: planet bodies, planet orbits or pendulum oscillation. But so are irregularities: rocks, coastlines, clouds, fixational eye movement.
And here is the discovery that influenced my interests and research topic a lot: fractal geometry. Fractals provide sort of evidence that irregular "things" can be described as simply as regular. But there is a small twist here!
For example take some long sequence of random (white noise) data. How to approximate those date ? Is there any simple recursive or any other equation that can describe this sequence or at least fit to it with a small error ?
Unfortunately, in general, it's almost impossible to find a short one. To give you more clue - white noise doesn't compress easily (just try JPG or ZIP on it).
But we can do something else with it. We change the way we think about approximation! Instead of trying to fit all the data, we can just try to reproduce their "general characteristics". Why not "approximate" white noise just by any other white noise, i.e. generated using simple LCG? If our application is audio-visual, we will not see much difference. This kind of reasoning was succesfully used in speech synthesisers or synthetic terrain/rocks generators. And taken to the extreme (applied to vast variety of signals) define what is called: procedural art.
A procedural technique researcher is trying to find methods (a set of rules, algorithms or equations) that can be used to generate very complicated signals that has the same "general characteristic" as modeled signals, while procedural artist is trying to "paint" with those methods.
I did several procedural works in my life, i.e. a movie inside weird caves and 64k intro, introducing my own procedural techniques.
More works like this can be found in so called demoscene archives, most recommended are some Inigo Quilez works. Another prominient researcher (not related to demoscene) is Dmytry Lavrov.
With a demoscene you have to be careful though: not all those little creations are fitting my procedural art definition. Some of them just use standard approximation techniques to describe regular "things" using subdivision surfaces, quantization, wavelet compression, etc... To put it straight, this creations have lower artistic value for me (but I'm not claiming they have no value at all).
Subscribe to:
Posts (Atom)
