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del

2007. 6. 19. 02:14 Method/Nature
Del is a vector differential operator.
Depending on the way del is applied, it can describe the gradient (slope), divergence (degree to which something converges or diverges) or curl (rotational motion at points in a fluid).

The image “http://upload.wikimedia.org/math/8/f/a/8fa511fbbd1188d080aacab402d9f7ae.png” cannot be displayed, because it contains errors.

http://en.wikipedia.org/wiki/Del_in_cylindrical_and_spherical_coordinates

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posted by maetel
2007. 6. 18. 21:07 Method/VFX
Jonathan T. Moon & Stephen R. Marschner
<Simulating Multiple Scattering in Hair Using a Photon Mapping Approach>

Program of Computer Graphics, Cornell University
Appears in ACM Transactions on Graphics 25:3
Proceedings of SIGGRAPH 2006


        > summary:

keywords:


The types of non-uniformities that can cause scattering, sometimes known as scatterers or scattering centers, are too numerous to list, but a small sample includes particles, bubbles, droplets, density fluctuations in fluids, defects in crystalline solids, surface roughness, cells in organisms, and textile fibers in clothing.

path tracing

multiple scattering
The main difference between the effects of single and multiple scattering is that single scattering can usually be treated as a random phenomenon and multiple scattering is usually more deterministic.
(Single scattering is therefore often described by probability distributions. With multiple scattering, the randomness of the interaction tends to be averaged out by the large number of scattering events, so that the final path of the radiation appears to be a deterministic distribution of intensity as the radiation is spread out.
The description of scattering and the distinction between single and multiple scattering are often highly involved with wave-particle duality.)

forward scattering
    http://en.wikipedia.org/wiki/Mie_theory
    Light Scattering Codes Library:  http://atol.ucsd.edu/scatlib

photon mapping

    Zack Waters' introduction

Monte Carlo method

density estimation

diffusion process

ray map
ray tracing

2p
Isotropy (the opposite of anisotropy) is the property of being independent of direction. Isotropic radiation has the same intensity regardless of the direction of measurement, and an isotropic field exerts the same action regardless of how the test particle is oriented.

Albedo is the ratio of reflected to incident electromagnetic radiation. It is a unitless measure indicative of a surface's or body's diffuse reflectivity.

Azimuth is the horizontal component of a direction (compass direction), measured around the horizon, from the north toward the east (i.e., clockwise) in astronomy and geodesy and from the south toward the west (i.e., clockwise) in surveying. It is usually expressed in degrees.
Azimuth is also terms used in mining for a similar, but slightly different angle: azimuths and meridian angles are used to name any angle measured clockwise from any meridian.

3p
solid angle Ω, that an object subtends at a point is a measure of how big that object appears to an observer at that point. For instance, a small object nearby could subtend the same solid angle as a large object far away. The solid angle is proportional to the surface area, S, of a projection of that object onto a sphere centered at that point, divided by the square of the sphere's radius, R. (Symbolically, Ω = k S/R², where k is the proportionality constant.) A solid angle is related to the surface area of a sphere in the same way an ordinary angle is related to the circumference of a circle.


(the outgoing radiance) = (the scattering function) * (the incident light distribution)

fiber tangent u

(incident light) = (direct light) + (scattered light)


Monte Carlo integration is numerical quadrature using pseudorandom numbers. That is, Monte Carlo integration methods are algorithms for the approximate evaluation of definite integrals, usually multidimensional ones. The usual algorithms evaluate the integrand at a regular grid. Monte Carlo methods, however, randomly choose the points at which the integrand is evaluated.
The traditional Monte Carlo algorithm distributes the evaluation points uniformly over the integration region. Adaptive algorithms such as VEGAS and MISER use importance sampling and stratified sampling techniques to get a better result.
E(f;N) = V \cdot \langle f \rangle = V\frac{1}{N} \sum_{i=1}^N f(x_i),
(Random sampling of the region may not uncover all the important features of the function, resulting in an underestimate of the error.)



ref.
<A conceptual model of the dehydration of air due to freeze-drying by optically thin, laminar cirrus rising slowly across the tropical tropopause>
Eric J. Jensen, Leonhard Pfister, Andrew S. Ackerman, and Azadeh Tabazadeh
NASA Ames Research Center, Moffett Field, California
Owen B. Toon
University of Colorado, Laboratory for Atmospheric and Space Physics, Boulder, Colorado   Journal of Geophysical Research, Vol. 106, N0. D15, Pages 17,237-17252, August 16, 2001
http://pubs.giss.nasa.gov/abstracts/2001/Jensen_etal.html
http://link.aps.org/abstract/PRA/v63/e052701


posted by maetel
2007. 5. 20. 01:20 Method/VFX
http://doi.acm.org/10.1145/357318.357320
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Willian T. Reeves <Particle Systems—a Technique for Modeling a Class of Fuzzy Objects>, ACM Transactions on Graphics, Vol.2, no.2, April 1983, Page 91-108


links:
LucanFilm Ltd.
Siggraph: Particle Systems


1
Particle systems model an object as a cloud of primitive particles that define its volume.
Stochastic processes are used to generate and control the many particles within a particle system.

The representation of particel systems :
  1. as clouds of primitive particles that define its volume (not by a set of primitive surface elements)
  2. depending on time (;changing form and moving with the passage of time)
  3. using stochastic processes (to create and change an object's shape and appeareance)

Advantages of the particle system over classical surface-oriented techinique :
  1. A particle is a much simpler primitive than polygon.
    • efficiency of computation time
    • easier removing temporal aliasing  effects (by Motion blurring of fast-moving objects)
  2. The model definition is procedural and is controlled by random numbers.
    • efficiency of human design time (to obtain a highly detailed model)
    • ability to adjust the level of detail (to suit a specific set of viewing parameters)
      • fractal surfaces
  3. It is easier to model "alive" objects changing form over a period of time.

keywords:
image synthesis
stochastic process
    Stochastics
fractal surfaces
procedure
random numbers
stochastic modeling
fractal modeling


2. BASIC MODEL OF PARTICLE SYSTEMS
A particle system is a collection of many minute particles that together represent a fuzzy object. Over a period of time, particles are generated into a system, move and change from within the system, and die from the system.

frame buffer =>
during each interval of time = at a given frame

    2.1 Particle Generation
NParts_f = (MeanParts_sa_f + Rand()*VarParts_sa_f)*ScreenArea
    MeanParts_sa_f = InitialMeanParts_sa + deltaMeanParts_sa*(f-f_0)

    2.2 Particle Attributes
initial position => the origin of a particle system
initial velocity
initial color <= average RGB values and the maximum deviation from them
initial transparency
initial size
shape => a region of newly born random particles about its origin
lifetime
A particle's initial color, transparency and size are determined by
mean values like MeasSpeed, maximum variations like VarSpeed of below:
InitialSpeed = MeanSpeed + Rand()*VarSpeed

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More complicated generation shapes based on the law of nature or on chaotic attractors have been envisioned.
    eg. streaked spherical shapes => motion-blur particles

    2.3 Particle Dynamics
    2.4 Particle Extinction
  • when a particle's lifetime reaches zero
  • when the intensity of a particle, calculated from its color and transparency, drops belowa specified threshold
  • when a particle moves more than a given distance in a given direction from the origin of its parent particle system
    2.5 Particle Rendering
        (1) Explosions and fire, the two fuzzy objects we have worekd with the most, are modeled well with the assumption that each particle can be displayed as a point light source. (Other fuzzy objects, such as clouds and water, are not.)
        (2) Since particles do not reflect but emit light, shadows are no longer a problem.
    2.6 Particle Hierarchy


3. USING PARTICLE SYSTEMS TO MODEL A WALL OF FIRE AND EXPLOSIONS
The Genesis Demo sequence from the movie Star Trek II: The Wrath of Khan was generated by the Computer Graphics project of Lucasfilm Ltd.

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The initial direction of the particles' movement was constrained by the system's ejection angle to fall within the region bounded by the inverted cone. As particles flew upward, the gravity parameter pulled them back down to the planet's surface, giving them a parabolic motion path. The number of particles generated per frame was based on the amount of screen area covered by the particle system.
Varying the mean velocity parameter caused the explosions to be of different heights.
The rate at which a particle's color changed simulated the cooling of a glowing piece of some hypothetical material.

When a motion picture camera is used to film live action at 24 frames per second, the camera shutter typically remains open for 1/50 of a second. The image captured on a frame is actually an integration of approximately half the motion that occurred between successive frames. An object moving quickly appears blurred in the individual still frames.

    ref. Tom Duff

    cf. seed value
 



4. OTHER PPLICATIONS OF PARTICLE SYSTEMS
    4.1 Fireworks

posted by maetel
2007. 4. 27. 18:48 Method/Nature
http://en.wikipedia.org/wiki/Riemann_sum



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For all ε > 0, there exists δ > 0 such that for any tagged partition x_0,...,x_n and t_0,...,t_{n-1} whose mesh is less than δ




    cp. epsilon-delta definition -> Cauchy definition (epsilon-delta)
       cp. Continuous function (topology)


cf.
topology 위상수학

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posted by maetel
2007. 2. 13. 02:13 Method/Cognition
Kristina Niedderer
­


Design Issues
Winter 2007, Vol. 23, No. 1, Pages 3-17
Posted Online December 11, 2006.
(doi:10.1162/desi.2007.23.1.3)

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2007. 1. 8. 02:27 Method/CG
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Ton DeRose, Michael Kass, Tien Truong <Subdivision Surfaces in Character Animation>


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posted by maetel
2006. 12. 11. 18:14 Method/IDE
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Peter Elsea <Visualization of Audio>

posted by maetel
2006. 11. 20. 13:01 Method/Drawing


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posted by maetel
2006. 10. 3. 23:13 Method/CG
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<Star Wars> 캐릭터 디자인


ref.
http://www.starwars.com/databank/species/geonosian/

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posted by maetel
2006. 9. 21. 01:25 Method/CG
사용자 삽입 이미지

봉준호 감독 <괴물>의 괴물 artwork

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posted by maetel
2005. 4. 25. 01:10 Method/Nature

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posted by maetel