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TOP THREE LINKS YOU MUST CLICK ON Advanced Java Casting Perlin's Movie Magic in Java3D
How Did They Do That?
By: Mike Jacobs
Mar. 9, 2005 12:00 AM
Reach behind your television and yank the cable out of the wall. Do you hear that noise? Not the kids screaming about their movie. Look at the screen. What you see is white noise: random bits of white, black and gray changing constantly. What does this have to do with movie magic or Java3D? What if a spell could conjure roaring fires, fluffy clouds, rippling water, naturally grained wood, smooth marble and even realistic terrains? That spell is available to us thanks to the inventive mind of Dr. Ken Perlin.
Who Was That Math Man?
What Was That Noise? To make realistic special effects, we need a way to generate natural looking randomness. You might think that random numbers would be sufficient to accomplish this, but you would only be partially right. (See Figure 1.) Random numbers are typically generated without regard to past values. This lack of correlation can lead to abrupt changes between adjacent values and an unnatural special effect. What we need is a repeatable, smooth, non-cyclic random function whose results vary with the parameters we provide. Perlin noise was designed to do just that. While the implementation details of Perlin noise are beyond the scope of this article, we do need a conceptual model to use it. The noise function accepts a number of double parameters and returns a double value between +1 and -1. One-dimensional noise is the result of generating random numbers at regular intervals and smoothly interpolating noise values in between using a high-order polynomial. This can be represented by a smooth curve as shown in Figure 1. Two-dimensional noise does the interpolation in two dimensions forming a wavy noise surface. The three-dimensional noise can't be depicted graphically, but its foundation is a lattice. The three parameters represent the three dimensions of the lattice from which the noise value is calculated. This lattice consists of 256 by 256 by 256 points representing random numbers between which values are smoothly interpolated to calculate the noise. The noise value at the integer lattice locations is zero, while the values between the locations follows the same high-order polynomial mentioned above. A Java reference implementation called ImprovedNoise is available from Dr. Perlin's home page and a modified version is included with the source code for this article. This probably sounds pretty mysterious, so let's put this magic to work with a few examples.
Casting Our First Spell: Blur In this example, the noise function is used to blur the boundaries between colors to make the transitions less apparent. The effect is implemented by nudging the color index with the noise function as shown in part in Listing 1. The color index is determined normally and then a delta value is calculated with the noise function. The sum of the index and the delta value is rounded and clamped to create the new color index. This method uses the row, column and elevation as arguments to the noise function. All three are scaled down to focus the noise based on trial and error. You can think of the divisors as a zoom function into the noise. Because the noise is defined in a limited-size lattice, the zoom factor focuses the range: higher zoom results in less noise range. Finding the right recipe for an effect is mostly an art but luckily others have shared their recipes.
Texturing with Noise Java3D supports texturing of a shape by setting the texture image on the appearance object. The PerlinNoiseSphere example uses a Java3D Sphere primitive as the shape and Perlin noise to generate the texture. The Sphere primitive is used in this example so some texturing details can be automatically done for us. Setting up the texture on the appearance is shown in part in Listing 2. The getImage() method is where the magic happens. The recipe is used to determine the noise values and the PerlinNoiseSphere example interprets the values as colors. Before I disclose the secret to this trick, I should mention that there's no relationship between how the recipe creates the texture and how nature creates the material. These recipes have been arrived at through trial and error and bit of luck. The results look amazingly close to the real thing, which teaches us that: In 3D graphics, there's nothing like a great fake. The recipe for the wood texture in Listing 3 is decidedly simple. The grain value is determined by the noise method using the image row and column as parameters. The color for the image pixel is based on the red, green and blue values calculated with the grain. Creating static texture images with noise is interesting, but the power of noise is even greater when combined with animation.
Animated Behavior When a behavior is created, the constructor typically defines the triggering or wake-up condition such as a keyboard or mouse event, a number of frames or the passage of time. Behaviors are added to the scene like any other Java3D object. When your scene is initially rendered, Java3D calls the initialize() method where your implementation should set the trigger. When Java3D detects the triggering event, it calls the processStimulus() method on your behavior. Your implementation of this method does its thing and then must reset the trigger. The documentation for the Behavior class is excellent, so refer to it for more details. The ElapsedTimeBehavior example is the basis for the animation examples in this article. When triggered, this behavior calls the tick() method on the configured listener after the specified number of milliseconds has passed. Milliseconds are used as the trigger rather than the number of frames so it runs consistently across different computers. Let's use this behavior to recreate the animation of a movie special effect in Java3D. YOUR FEEDBACK
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