Taking a break…: “

The magnetosphere project was getting away from me. It happens. It was option overload. So many things I wanted to do with it. My fuses got blown. So I decided to get back to my roots.

One of my first interests when I started working with Processing was the simple beauty of Perlin noise. I am not going to get into the explanation of Perlin noise for two simple reasons.

1) Its after midnight and I should start thinking about getting to bed.
2) I dont really understand it enough to explain it.

What I can say is that noise() in Processing will give you a smoothly changing set of numbers from 0.0 to 1.0 based on Perlin’s noise algorithm. Combined with the new-found wonderfulness of Shiffman’s Vector Library for Processing, I decided to take another stab at making a 3D flowfield based on Perlin noise.

I had attempted it a couple years back and had some decent results, but the z-axis part of it never quite made it over to the left side of my brain so I shelved it for a later attempt. That attempt happened tonight.

Okay, lets see if I can explain what is going on so when you view the video linked at the end of this post, you will get what I was going for.

First, I took short movie, in this case, a movie of me waving a cellphone in front of my iSight. It was short… 33 frames. I brought these frames into Processing and put them into a PImage array. These images were then rendered out in space from back to front so I ended up with a cube of images. The point wasnt to show these images, but I put them there for effect and for testing. The actual goal was to do three dimensional flow-field painting with several thousand particles.

Okay, so I made a 3D flow-field. With any luck and a little free time, I will get into the details of it at some point this week. This flow-field basically allows me to drop objects into the space and they will move based on the 3D vector which is closest to it. Think of a 3D space filled with arrows. The arrows tell objects near them which way to travel. The orientation of these arrows is based on Perlin noise. Throw 10,000 objects into this arrow field and you end up with a nice faux-flocking behaviour.

The images come into play when I color the objects moving through this space. Each object compares its position in the 3D space with the images in the 3D space and grabs the color from the pixel it is closest to.

I did a quick render of the thousands of objects moving through this space. It turned out fairly well. The next step is to use a webcam history instead of using a precanned video. I dont think the images will be all that recognizable, but the colors will cycle nicely.

Click here to view the quicktime.

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[tags]coding, processing, java, 3d, generated[/tags]

(Via all manner of distractions.)