H. Nishimura, M. Hirai, T. Kavai et al., "Object modeling by distribution function and a method of image generation", Transactions of IECE J68-D, n. 4, p. 718725, 1985.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....primitive) and by creating new implicit functions using the sum, min, or max of simpler functions. The final object is constructed by blending the primitives, and as primitives are moved and deformed the resulting blended surface changes shape. Some types of implicit surfaces like metaballs [21], blobs [4] convolution surfaces [5] or soft objects [39] have received increasing attention in Computer Graphics. Nowadays, an important trend in representation of deformable objects is the use of implicit surfaces mixed with particle systems, as we can see in [11] Physically based models are ....

Nishimura, H., Hirai, M., Kavai, T. et al. "Object modeling by distribution function and a method of image generation", Transactions of IECE J68-D, n. 4, p. 718-725, 1985.

....Surfaces Implicit surfaces [19] are defined by isosurfaces of a function. Their main use is in scientific visualization. Implicit surfaces arise naturally in many physical simulations, such as simulation of liquids [17] They have also been used as a modeling primitive in the form of metaballs [40]. The main drawback of implicit surfaces is that they are hard to render efficiently, because evaluating points on a surface requires numerical root finding. An implicit surface can be rendered directly by ray tracing [19] by converting it into a polygon mesh [7] or a point based ....

Hitoshi Nishimura, Makoto Hirai, Toshiyuki Kawai, Toru Kawata, Isao Shirakawa, and Koichi Omura. Object modeling by distribution function and a method of image generation. In Electronics Communication Conference '85, pages 718--725, 1985.

....implicit functions using the sum, min, or max of simpler functions. The final object is constructed by blending the primitives, and as the primitives are moved and deformed the resulting blended surface changes shape. A particular subset of implicit surfaces, called soft objects [3] or metaballs[4], blobs [5] convolution surfaces [6] have received increasing attention in computer graphics. We have developed an interactive system, named Body Builder , for interactive design human bodies from scratch or by modifying existing models. Ellipsoidal metaballs and ellipsoids are employed to ....

Nishimura H., Hirai M., Kawai T., et al ."Object modeling by distribution function and a method of image generation", Trans. IECE, J68-D(4), 1985, pp.718- 725.

....objects. Shapes of any topology can be easily created using several primitives that blend their field function contributions. Moreover, local and global deformations can be incorporated in the construction tree. However, although they have been introduced in Computer Graphics for many years now [2, 12, 21], implicit surfaces are not as popular as parametric surfaces for performing modeling tasks. One of the main problems is the lack of parameterization which makes the interaction with implicit shapes very difficult. The second problem is the high cost, in the general case, of the calculation of the ....

H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, and K. Omura. Objects modeling by distribution function and a method of image generation (in japanese). The Transactions of the Institute of Electronics and Communication Engineers of Japan, J68-D(4):718--725, 1985.

....a scalar eld function and iso is the value at which the iso surface is drawn. An evaluation of the eld function at any point permits the inside outside test which simpli es computations for controlled blending, collision detection and ray tracing. The eld function can be generated by points [1, 10, 15] or by more complex geometric primitives (such as line segments or triangles) that form a skeleton. The skeleton, surrounded by its implicit skin, provides an intuitive way of controlling aspects of an object in a modelling or animation environment [8, 4] There are two main ways to de ne an ....

H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, and K. Omura. Objects modeling by distribution function and a method of image generation (in japanese). The Transactions of the Institute of Electronics and Communication Engineers of Japan, J68-D(4):718-725, 1985.

....0.8 1 Figure 7: The function C(r 2 ) plotted over r: 3 Polynomials Root finding is much easier on nicer functions, like polynomials. Hence, there havebeen several polynomial approximations to the Gaussian distribution to make implicit surface rendering more efficient. 3. 1 Metaballs In [Nishimura et al. 1985], the function H(t) is approximated piecewise by quadratics. The individual components, the F and G# are eachapproximated by four quadratic curves. Their combination H is then segmented and each segment is represented by the quadratic resulting from the sum of the component quadratics. During ....

Nishimura, H., Hirai, M., Kawai, T., Kawata, T., Shirakawa, I., and Omura, K. Object modeling by distribution function and a method of image generation. In Proceedings of Electronics Communication Conference '85, pages 718--725, 1985. (Japanese).

....only study the structure of fluid dynamics in a free space. Some methods have been developed to represent the boundary (e.g. seashore) between fluid and solid. However, those previous methods had some technical problems to make a realistic model for small mass of the fluids like a water droplet[Nishi83a]. In order to represent a soft object like liquid, the metaball has widely been used since it was defined by a few simple implicit formula and it allows simple free form deformation operations[Wyvil86a, Wyvil90a] Especially most of human bodies(e.g. hands, arms, foot and muscular form) are ....

....of each point is determined by distance from specified center point of metaball. The task of the user is to specify the center position of each metaball, radius and field function. This metaball technique was first developed by Blinn, and he called it blobs. And this was improved by Nishimura[Nishi83a], Murakami[Murak87a] and Wyvill[Wyvil86a] et al. They called it metaball and soft objects. The main differences in these previous works are in the shape of field functions and the methods solving for ray isosurface intersections. For n different metaballs, the shape of the curved surface is ....

Nishimura,H et al.: Object Modeling by Distribution Function and a Method of Image generation, In Journal of the Electronics Communication Conference '85, J68D (4),pp.718-725,1987

.... for modeling electron density formed the blobby model in computer graphics that allowed the user to freeform model a surface by placing automatically blending spheres near each other [Blinn, 1982] These blobby models were made efficient with piecewise polynomial approximations with finite support [Nishimura et al. 1985; Wyvill et al. 1986] A variety of blending methods have been devised for other primitives and with more sophisticated smoothness properties [Hoffman Hopcroft, 1985; Rockwood Owen, 1987] Implicit surfaces offer a free form modeling methodology. Modeling environments for implicits have also ....

Nishimura, H., Hirai, M., Kawai, T., Kawata, T., Shirakawa, I., and Omura, K. Object modeling by distribution function and a method of image generation. In Proc. of Electronics Communication Conference '85, 1985, pp. 718--725. (Japanese).

....flaw in [Blinn, 1982] is an ad hoc root isolation phase. 3 Polynomials Root finding is much easier on nicer functions, like polynomials. Hence, there have been several polynomial approximations to the Gaussian distribution to make implicit surface rendering more efficient. 3. 1 Metaballs In [Nishimura et al. 1985], the function H#t# is approximated piecewise by quadratics. The individual components, the F and G; are each approximated by four quadratic curves. Their 4 4 2 2 4 6 8 10 0.75 0.5 0.25 0.25 0.5 0.75 1 Figure 4: Newton s method for finding roots of H(t) At t # # #:# Newton s method ....

Nishimura, H., Hirai, M., Kawai, T., Kawata, T., Shirakawa, I., and Omura, K. Object modeling by distribution function and a method of image generation. In Proc. of Electronics Communication Conference '85, 1985, pp. 718--725. (Japanese).

....two groups who were unaware of each others work independently discovered this new method of representing surfaces. Both James Blinn and Hitoshi Nishimura and his co workers realized that a surface can be modeled using an implicit function that is the sum of several Gaussian radial basis functions [3, 16]. Such models (sometimes called blobbies or metaballs) have been used in a number of animations, including The Great Train Rubbery, the blood floating in zero gravity in Star Trek VI, and the creatures in Flubber. Despite these successes, blobby implicit surfaces are seldom the method of choice ....

H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirkawa, and K. Omura. Object modeling by distribution function and a method of image generation. Transactions of the Institute of Electronics and Communication Engineers of Japan, J68D (4):718--725, 1985.

....of such a usefulness, many commercial software packages implement metaball modeling techniques. The metaball technique has become an indispensable technique in 3 D graphics software. This modeling technique was first developed by Blinn[Blinn80] who called it blobs. In Japan, Nishimura et al. Nishim85] developed it independently, and called it metaballs. 5.1 Field function In the metaball technique, a free form surface is defined as an isosurface (equi potential surface) of a field function. The field value at any point is defined by distances from the specified points in space. We used the ....

H. Nishimura, M.Hirai, T.Kawai, T.Kawata, I.Shirakawa, K.Omura, Object Modeling by Distribution Function and a Method of Image generation,", Journal of papers given by at the Electronics Communication Conference'85 J68-D(4) pp.718-725 (in Japanese).

....with continuous first and second derivatives, and its implicit surface must be a manifold, without any cusps, kinks or creases. These restrictions include exponential based blobby models [Blinn, 1982] but exclude some of the more 213 efficient C 1 piecewise polynomial approximations [Nishimura et al. 1985; Wyvill et al. 1986] The implicit surface is extended into a family of surfaces defined by f(x; q) continuously parameterized by the vector q consisting of various model parameters (e.g. the locations of blobby elements) For some values of q; the implicit surface defined by f(x; q) 0 may ....

Nishimura, H., Hirai, M., Kawai, T., Kawata, T., Shirakawa, I., and Omura, K. Object modeling by distribution function and a method of image generation. In Proc. of Electronics Communication Conference '85, 1985, pp. 718--725. (Japanese).

....X k i 2S OE i (M) where OE i is a local function defined in a neighborhood of k i . Different authors have proposed variations on this formulation: ffl Blinn [3] uses a formulation where OE i is defined by an exponential. The resulting objects are called Blobby Models, ffl Nishimura and al. [15] use a polynomial expression for OE i . The implicit contours obtained this way are often called Metaballs, ffl Wyvill and al. 24] use another polynomial formulation. The resulting objects are called Soft Objects. This is the formulation we are going to use in this paper. We describe it in more ....

H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, and K. Omura. Objects modeling by distribution function and a method of image generation (in japanese). Trans. IEICE, J68-D(4):718--725, 1985.

....techniques based on hierarchical representations are much more suitable. The algorithms also depend on the object being rigid, and are hence unsuitable for collision detection between deformable objects. Implicit Surfaces, where a scalar field function is used to define the shape of an object [1, 14, 34], are commonly used to model objects which deform, split or blend. Seeds may be used to produce a set of polygons that fit the surface at run time [5] A method of producing piecewise contact allows collision detection and its subsequent response [7] However, the polygonisation methods used are ....

Nishimura H Hirai MKawai T Kawata T Shirakawa I and Omura K. Object modeling by distribution function and a method of image generation. volume 68, pages 718--725, 1995.

....= 1 x . Points on the sphere are those locations at which f (x) 0. This implicit function takes on positive values interior to the sphere and is negative outside the surface, as will be the convention in this paper. An important class of implicit surfaces are the blobby or metaball surfaces [3, 19]. The implicit functions of these surfaces are the sum of radially symmetric functions that have a Gaussian profile. Here is the general form of such an implicit function: f (x) t n i=1 h i (x) 1) In the above equation, a single function h i describes the profile of a blobby sphere that ....

....and thus is the control over the radius of a blobby sphere. The center of a blobby sphere is given by c i . Evaluating an exponential function is computationally expensive, so some authors have used piecewise polynomial expressions instead of exponentials to define these blobby sphere functions [19, 31]. A greater variety of shapes can be created with the blobby approach by using ellipsoidal rather than spherical atomic functions. Another important class of implicit surfaces are the algebraic surfaces. These are surfaces that are described by polynomial expressions in x, y and z. If a surface ....

Hitoshi Nishimura, Makoto Hirai, Toshiyuki Kawai, Toru Kawata, Isao Shirkawa, and Koichi Omura. Object modeling by distribution function and a method of image generation. Transactions of the Institute of Electronics and Communication Engineers of Japan, J68D (4):718--725, 1985.

....functions is the addition. One immediate practical implication is that, if the functions are carefully chosen, then any resulting implicit object can be guaranteed to be bounded. The more widely used techniques based on the skeleton approach are Blobs[28] Soft Objects [31] and Metaballs [30]. Their main difference resides in the scalar function used to define their component scalar fields. 6.1.2 A New Proposal Malheiros[29] proposed a new variant for skeleton based modeling. In this approach, an object can be implicitly given by the equation F (x) c; where F is the function ....

Nishimura, H., Hirai, M., Kawai, T., Kawata, T., Shirakawa, I. e Omura, K. Object Modeling by Distribution Function and a Method of Image Generation, Japan Electronics Communication Conference 85, 1985

....of a sphere, recent use of this class of surfaces computes a scalar field based on a function of distance from a skeleton of primitives. The primitives are generally lines, points, circles etc. These techniques were introduced by Blinn [5] and refined by Wyvill et al. 11] and Nishimura et al. [8]. A common formulation is shown in function 2. f#r# = 8 # : 1 r#0 , 1, 4 9 r 2 #, 1,r 2 # 2 0#r#1 0 r#1 (1) F #p# = i#=n X i=1 f i #jpj# (2) Where p is the point #x; y; z#,andf i is the field function for the i th skeleton in the composite implicit surface. The function used ....

....distance metric. In section 4 we discuss how to use these general distance metrics in non point skeleton implicit surfaces. Some results are shown in section 5 and conclusions and future work are outlined in 6. 2 Previous Work The framework described in the original work on implicit surfaces [5, 11, 8] defines the surface as a level set of an implicit function F #x; y; z# = 0, and yielded shapes that had a spherical offset surface. This is to say that a point skeleton yields a sphere, a line skeleton yields a cylinder with hemispherical caps, a circle yields a torus, etc. This is a result (a) ....

H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, and K. Omura. Object modeling by distribution function and a method of image generation. Trans. IECE Japan, Part D, J68-D(4):718--725, 1985.

.... z 2 , 1. Recent use of this class of surfaces computes a scalar field based on a function of distance from a skeleton of primitives. The primitives are generally lines, points, polygons etc. These techniques were introduced by Blinn [3] and refined by Wyvill et al. 20] and Nishimura et al. [11]. For the purposes of this paper we restrict the class of implicit surfaces to skeleton based surfaces in accordance to those defined separately by Wyvill [3] The definition of Blinn [3] uses an exponential function to define the scalar field. The exponential field function is not in widespread ....

H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, and K. Omura. Object modeling by distribution function and a method of image generation. Trans. IECE Japan, Part D, J68-D(4):718--725, 1985.

....with continuous first and second derivatives, and its implicit surface must be a manifold with a well defined, continuously varying surface normal. These restrictions include exponential based blobby models [1] but exclude some of the more efficient C 1 piecewise polynomial approximations [21, 36]. The implicit surface is extended into a family of surfaces defined by f(x; q) continuously parameterized by the vector q consisting of various model parameters (e.g. the locations of blobby elements) For some values of q; the implicit surface defined by f(x; q) 0 may contain a cusp, kink or ....

NISHIMURA, H., HIRAI, M., KAWAI, T., KAWATA, T., SHI- RAKAWA, I., AND OMURA, K. Object modeling by distribution function and a method of image generation. In Proc. of Electronics Communication Conference '85 (1985), pp. 718-- 725. (Japanese).

....surface detail without changing the underlying geometry. Texture mapping is closely tied to surfaces described parametrically, such as patches, since the mapping of two parametric spaces is usually straightforward. Implicit surfaces, i.e. those defined by an iso contour of an implicit function [2, 14, 7], present a major difficulty in that implicit surfaces do not have a natural coordinate system defined on them. Since an implicit surface cannot be easily parameterized, a common way to apply textures onto it is to use solid textures [8, 9, 15] Although 3D texture mapping is a powerful technique, ....

H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, K. Omura, Object modeling by distribution function and a method of image generation. Trans. IECE Japan, Part D J68-D(4), pp 718--725, 1985.

....Geometric Modeling, Photo realism 1 Introduction The representation of free form surfaces can be classi ed into two: parametric surfaces and implicit surfaces. For the former, B ezier patches, B spline patches, and NURBS are used. For the latter, a set of density functions such as metaballs[4] (blobs[1] or soft objects[11] is often used; in this method, a curved surface is de ned by an isosurface which is a set of points having the equi potential eld value. The eld value at any point is de ned by distances from the speci ed points in space. The features of the metaballs are as ....

....distances from the speci ed points in space. The task of the user is to specify the center position of each metaball, its density at the center, eld function, and color. This modeling technique was rst developed by Blinn[1] and he called it blobs (or blobs molecules) In Japan, Nishimura et al.[4] independently developed it, and they called it metaballs. Recently Wyvill et al. 9] 10] 11] have also developed a display method for eld functions, and he called it soft objects. The main di erences in these previous work are in the shapes of eld functions and the methods solving for ....

[Article contains additional citation context not shown here]

H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, K. Omura, \Object Modeling by Distribution Function and a Method of Image generation,", Journal of papers given by at the Electronics Communication Conference '85 J68-D(4) pp.718-725 (in Japanese).

....to evaluate, requiring only three additions and five multiplications. Furthermore, because of their limited scope, only the local primitives need to be considered when evaluating a specific point in space. Metaballs are another piecewise polynomial approximation to Blinn s exponential functions [29]. They use piecewise quadratic functions, and are very common in commercial modeling packages today. 2.1.3. A New Blending Function The Morse theorems used in this dissertation demand an infinitely differentiable surface. Aside from the stringent theoretical requirements (which may not be ....

H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, and K. Omura. Object modeling by distribution function and a method of image generation. Trans. IECE Japan, Part D, J68-D(4):718--725, 1985.

....with continuous first and second derivatives, and its implicit surface must be a manifold, without any singularities, kinks or creases. These restrictions include the exponential based blobby model of Blinn [1982] but exclude some of the more efficient C 1 piecewise polynomial approximations [Nishimura et al. 1985; Wyvill et al. 1986] Algebraic surfaces and CSG models created using R functions [Pasko et al. 1995] fall within this scope. The implicit surface is extended into a family of surfaces defined by f(x; q) continuously parameterized by the vector q consisting of various model parameters (e.g. ....

Nishimura, H., Hirai, M., Kawai, T., Kawata, T., Shirakawa, I., and Omura, K. Object modeling by distribution function and a method of image generation. In Proc. of Electronics Communication Conference '85, 1985, pp. 718--725. (Japanese).

....0.6 0.8 1 Figure 7: The function C(r 2 ) plotted over r: 3 Polynomials Root finding is much easier on nicer functions, like polynomials. Hence, there have been several polynomial approximations to the Gaussian distribution to make implicit surface rendering more efficient. 3. 1 Metaballs In [Nishimura et al. 1985], the function H(t) is approximated piecewise by quadratics. The individual components, the F and G; are each approximated by four quadratic curves. Their combination H is then segmented and each segment is represented by the quadratic resulting from the sum of the component quadratics. During ray ....

Nishimura, H., Hirai, M., Kawai, T., Kawata, T., Shirakawa, I., and Omura, K. Object modeling by distribution function and a method of image generation. In Proceedings of Electronics Communication Conference '85, pages 718--725, 1985. (Japanese).

.... [Blinn, 1982] Soft objects approximate Gaussian distribution with a sixth degree polynomial to avoid square roots and exponentiation [Wyvill et al. 1986] Metaballs approximate Gaussian distribution with piecewise quadratics to avoid square roots, exponentiation and iterative root finding [Nishimura et al. 1985]. Sphere tracing likes distance, and avoids nothing. Soft Object In [Wyvill et al. 1986] the following cubic in distance C(r) 2 r 3 R 3 Gamma 3 r 2 R 2 1 (22) approximated a Gaussian distribution, but was rejected for a sixth order cubic in distance squared. Repeated ....

Nishimura, H., Hirai, M., Kawai, T., Kawata, T., Shirakawa, I., and Omura, K. Object modeling by distribution function and a method of image generation. In Proceedings of Electronics Communication Conference '85, pages 718--725, 1985. (Japanese).

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H. Nishimura, M. Hirai, T. Kavai et al., "Object modeling by distribution function and a method of image generation", Transactions of IECE J68-D, n. 4, p. 718725, 1985.

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Nishimura H, Hirai M, Kawai T. Object modeling by distribution function and a method of image generation. Transactions on IECE 1985;68-D(4):718}25.

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H. Nishimura, M. Hirai and T. Kawai. "Object Modeling by Distribution Function and a Method of Image Generation." Transactions on IECE, 68-D(4):718-725 (1985)

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H. Nishimura, M. Hirai, and T. Kawai, "Object Modeling by Distribution Function and a Method of Image Generation", Transactions on IECE, Vol.68-D, No.4, 1985, pp.718~725,

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H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, K. Omura, "Object Modeling by Distribution Function and a Method of Image generation,", Journal of papers given by at the Electronics Communication Conference '85 J68-D(4) pp.718-725 (in Japanese)

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H. Nishimura et al. Object Modeling by Distribution Function and a Method of Image Generation. In Journal od papers given at the Electronic Communication Conf., 1985.

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Hitoshi Nishimura, Makoto Hirai, Toshiyuki Kawai, Toru Kawata, Isao Shirkawa, and Koichi Omura. Object modeling by distribution function and a method of image generation. Transactions of the Institute of Electronics and Communication Engineers of Japan, J68-D(4):718--725, 1985.

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H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, K. Omura, Object modeling by distribution function and a method of image generation. Trans. IECE Japan, Part D J68-D(4), pp 718--725, 1985.

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H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, and K. Omura. Object modeling by distribution function and a method of image generation. Transactions IECE Japan, Part D, J68-D(4):718--725, 1985.

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H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, and K. Omura. Objects modeling by distribution function and a method of image generation (in japanese). T'ars, IEIGE dapar, J68-D(4):718 725, 1985.

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H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, and K. Omura. Objects modeling by distribution function and a method of image generation (in japanese). The Transactions of the Institute of Electronics and Communication Engineers of Japan, J68-D(4):718-- 725, 1985.

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. 18. H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, and K. Omura, "Objects modeling by distribution function and a method of image generation

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H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, and K. Omura. Objects modeling by distribution function and a method of image generation (in japanese). The Transactions of the Institute of Electronics and Communication Engineers of Japan, J68-D(4):718--725, 1985.

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H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, and K. Omura. Objects modeling by distribution function and a method of image generation (in japanese). The Transactions of the Institute of Electronics and Communication Engineers of Japan, J68-D(4):718--725, 1985.

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H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, and K. Omura. Objects modeling by distribution function and a method of image generation (in japanese). The Transactions of the Institute of Electronics and Communication Engineers of Japan, J68-D(4):718--725, 1985.

No context found.

Nishimura, H., Hirai, M., Kawai, T., Kawata, T., Shirakawa, I., and Omura, K. Object modeling by distribution function and a method of image generation. In Proc. of Electronics Communication Conference '85, 1985, pp. 718--725. (Japanese).

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H. Nishimura, M. Hirai, T. Kawai, T. Kawata, I. Shirakawa, and K. Omura. Object modeling by distribution function and a method of image generation. Transactions IECE Japan, Part D, J68-D(4):718--725, 1985.

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